We’re looking for a Full-Stack Engineer who actually enjoys owning a product after it ships, not just building features, merging a PR, and disappearing into the internet. Our web app is already live, already has paying/active users, and is continuing to grow. The foundation is there. What we need now is an experienced engineer who can learn the existing system, keep it healthy, solve the weird problems that inevitably show up in production, and help us scale without turning the codebase into a haunted house six months from now. We also work a little differently. Our development process is heavily AI-assisted. We use Claude along with a dedicated AI engineering agent that helps monitor the application, troubleshoot issues, and handle development work. We’re not looking for someone who feels threatened by that, or someone who blindly accepts whatever the AI spits out because “the tests passed.” We want the human in the loop who knows when the AI is right, when it’s confidently wrong, and when a problem needs actual engineering judgment. The Current Stack You’ll be working with: Supabase — database, authentication, and backend services Railway — deployment and production infrastructure Claude + AI engineering tools — development, debugging, and monitoring Whop — plus other third-party APIs and integrations A live production application with real users and real-world edge cases What You’ll Own You’ll become the technical owner and escalation point for the application. That means keeping production stable, investigating bugs, handling customer-reported technical issues, and stepping in when our AI engineering agent hits something it can’t reliably solve. You’ll review AI-generated code when needed, trace issues across the frontend, backend, database, authentication, APIs, and third-party integrations, and implement new features and improvements as the product evolves. We also want someone proactive enough to spot smoke before the kitchen is on fire. That includes monitoring performance and reliability, improving logging and observability, tightening testing and deployment processes, reviewing security and data integrity, checking backups and recovery processes, cleaning up technical debt, and recommending architecture changes when the current setup starts reaching its limits. Just as importantly, you should be able to explain what’s happening to a non-technical founder without requiring a 47-slide architecture deck. You’ll Probably Be a Great Fit If You... Have strong full-stack experience and have maintained real production applications with real users, not just demos or side projects. You should be comfortable jumping into an unfamiliar codebase and figuring out how the pieces connect without needing everything explained line by line. Strong experience with Supabase, SQL/databases, APIs, authentication, third-party integrations, deployments, debugging, and production troubleshooting is important. Experience with Railway is a big plus, although experience running applications on similar cloud platforms translates well. You should also be comfortable working with AI development tools such as Claude, Cursor, GitHub Copilot, or similar tools. The important part isn’t simply knowing how to prompt them. We want someone capable of reviewing AI-generated code critically, catching bad assumptions, identifying security or scalability problems, and deciding what should—and absolutely should not—make it into production. Experience with SaaS products, membership platforms, customer-facing applications, or startup environments is especially useful. Strong English communication matters too. You’ll be working directly with a non-technical founder, so being able to turn “something weird happens when customers do X” into a root cause and sensible solution is part of the job. Hours & Compensation This will start at approximately 20-30 hours per week, at $70-$90 USD/hour, with the intention of building a long-term working relationship. Most normal weeks will probably be closer to five hours. When we’re shipping a larger feature, improving infrastructure, or chasing down an especially stubborn production gremlin, additional hours will be available. We’re particularly interested in engineers based in Latin America because U.S. time-zone overlap makes collaboration easier, but location isn’t a hard requirement. If you’re excellent, reliable, and communicate well, we’re happy to hear from you wherever you’re based. As the product and customer base grow, there’s plenty of room for the role—and the number of hours—to grow with it. When You Apply Please keep it straightforward. Tell us about one live production application you’ve maintained or taken technical ownership of, what the stack looked like, and one difficult production issue you personally diagnosed and solved. Also tell us about your experience with Supabase/Railway and how you currently use Claude, Cursor, Copilot, or other AI coding tools in your development workflow. No need for a novel. We’d much rather hear about a messy production problem you actually solved than read another paragraph about being a “results-driven technology professional.”

*** DO NOT APPLY IF YOU CAN NOT DO AT LEAST 95% OF THE JOB DESCRIPTION*** We're looking for a battle-tested engineer with deep, self-earned coding fundamentals who also knows how to leverage AI as a force multiplier. This is not a role for developers who have grown dependent on AI to write code they couldn't write themselves. You should be able to navigate a large, complex brownfield codebase on your own — and when you do bring AI into the work, your engineering foundation is what makes the difference between AI generating noise and AI generating production-ready solutions. This role is deliberately vertical. You'll write product code, and you'll own the AWS environment it runs on. Those aren't two jobs handed to one person to save a headcount — they're one job, because the interesting failures happen at the seam between them. ## About the Role You'll work across a TypeScript codebase with a Next.js frontend and AWS-backed services supporting consumer mobile applications at meaningful scale. AI tools are a deliberate part of the workflow: prompting for implementation plans, critically evaluating those plans against our architecture and business requirements, reviewing generated code for correctness and quality, and shipping with confidence. When AI hits the limits of a complex legacy system — and it will — you'll be the one who knows how to guide it through. On the platform side, you'll own infrastructure defined in code, the network boundaries around our data services, our cloud security posture, and the vulnerability backlog. The systems you'll inherit include an event-driven ingestion pipeline (managed queues and a key-value store behind an API gateway), a columnar analytics warehouse feeding BI dashboards, object storage with a query layer over it, a document database, and webhook integrations with third-party attribution and app-store billing systems. That's real scope, and we're stating it plainly so you can decide whether you want it. If you'd rather not touch infrastructure, this isn't the role. If you've been looking for a job where you own the whole vertical instead of filing tickets across a boundary, it is. ## What You'll Do ### Product engineering - Own the full lifecycle of AI-assisted development: generating plans, stress-testing them against real architectural constraints, and validating that generated code is production-worthy - Write correct concurrent code: reason clearly about async/await, the event loop, promise scheduling and cancellation, and the difference between concurrency and parallelism — and keep blocking work off the request path so a slow upstream API never stalls the thread serving users - Make and defend architectural decisions: know where layered, clean, and hexagonal (ports-and-adapters) designs each earn their complexity, enforce separation of concerns, and keep AI-generated solutions inside the boundaries the codebase already established rather than letting them drift toward whatever pattern the model saw most often in training - Practice test-driven development in earnest — write the failing test first, make it pass, then refactor — and use TDD as the mechanism that keeps AI-generated code honest rather than a box to check afterward - Drive tests past the happy path: use AI to enumerate boundary values, error branches, race conditions, malformed input, and failure modes of dependencies, then verify the generated tests actually assert behavior instead of restating the implementation back at itself - Contain the blast radius of AI-assisted work: small reviewable diffs, plans before code, incremental commits, contract and regression coverage on anything touching shared surfaces, and a bias toward changes you can reason about end to end - Build and maintain the backend services behind our mobile applications, including event ingestion, third-party webhook consumers, and the integrations that feed reporting ### Platform and infrastructure - Define and change infrastructure as code: extend and review Terraform modules, manage state, read a plan critically before applying it, and recover when state and reality disagree - Own cloud networking: private and public subnets, security group and NACL design, and the access patterns for data services that sit inside the network — with a clear view of when putting compute in a VPC is the right call and when it just buys cold starts and NAT charges - Design read and write paths for scale, cost, and exposure: when something is hammering an object store or an API, diagnose whether it's legitimate traffic or an unsecured origin being scanned, and reach for the fix that matches — edge caching, cache-control and conditional requests, presigned URLs with sane TTLs, request collapsing, batching and backpressure on one side; blocking public access, origin access control, bucket policy and IAM scoping, WAF rate limiting, and keeping repository metadata and build artifacts out of served paths on the other - Treat a surprising cloud bill as a security signal, not just a cost problem — know which request outcomes you're billed for, what shows up in access and audit logs, and when the right response is rotating credentials rather than adding a cache - Own and tune cloud security posture management (AWS Security Hub, GuardDuty, Config, or equivalents): configure the standards, suppress the noise so real signal survives, and drive findings to closed - Apply and enforce security best practices aligned with NIST controls, including access control, audit logging, system integrity, and secure configuration management — using automated config checks to continuously verify those controls rather than attesting to them in a document nobody re-reads - Manage IAM as a design problem: least-privilege roles, scoped policies, credential rotation, and no long-lived keys where a role will do - Own CI/CD: pipelines that gate on tests, coverage, and security scans, with deploys that are reproducible and reversible ### Vulnerability management - Remediate CVEs, don't just report them. Take findings from discovery through to a shipped fix, including the unglamorous part where the patched version is a major bump and you absorb the breaking changes across the application - Triage with judgment: knowing whether a finding is reachable in code paths we actually execute or buried in a transitive dependency that never runs is what keeps you from breaking production over a theoretical risk. But the deliverable is a closed finding, not an assessment - Maintain dependency hygiene across a large Node/TypeScript tree, where the vulnerability surface is mostly transitive and the fixes are mostly version bumps with consequences - Remediate infrastructure and configuration findings, not just application dependencies — misconfigured storage, over-permissive policies, unencrypted resources, missing logging ### Operations - Serve as a rapid-response resource for user-facing issues — diagnosing, prototyping, and deploying fixes fast when production is on the line - Leave the environment legible to someone else: documented infrastructure, runbooks for the things that page you, and reproducible deploys. Sole ownership only works if it isn't sole knowledge ## What We're Looking For - 5+ years of proven TypeScript development experience, with work you can walk us through line by line and explain the reasoning behind — you know the language, not just the prompts - Deep proficiency in React and Next.js - Fluency in the JavaScript concurrency model, and enough exposure to how other ecosystems solve the same problem (C# tasks, Python asyncio, Kotlin coroutines, Rust futures, Go goroutines) to explain what async/await actually buys you and where it doesn't help - Demonstrated experience with TDD and a clear point of view on what it's good for and where it isn't worth it - The ability to reason about architectural tradeoffs out loud — not just name patterns, but say what each one costs and when you'd skip it - Strong working knowledge of AWS across compute, managed queues, key-value and relational stores, object storage, CDN, WAF, and IAM — including request-pattern and caching design under load and hardening of publicly reachable origins - Hands-on Terraform experience: writing and reviewing modules, managing state, and recovering from drift. Other IaC backgrounds (CDK, CloudFormation, Pulumi) transfer if the depth is there - Practical cloud networking: VPCs, subnet architecture, security groups, NACLs, and private connectivity to managed data services - Experience running a cloud security posture tool in anger — configuring standards, tuning findings, mapping automated checks to a control framework, and closing items rather than accumulating them - A demonstrated CVE remediation history: specific vulnerabilities you personally fixed, in both application dependencies and infrastructure configuration, including at least one where the fix required meaningful refactoring - Working fluency with SCA tooling (AWS Security Hub, Prowler, Dependabot, Snyk, npm audit, or similar) and a defensible process for prioritizing what gets fixed - The ability to critically read and evaluate AI-generated code — catching architectural drift, security gaps, and subtle logic errors that AI won't flag itself - A specific, experience-backed account of where AI coding tools fail: missing system-wide context, no real model of your codebase's complexity or layering, confidently wrong abstractions, tests that validate the bug, and volume that outpaces review capacity — plus the practices you use to keep that in check - Familiarity with AWS Security Hub, CIS Benchmarks, NIST or comparable security frameworks and the ability to translate controls into practical engineering decisions - Comfort using AI tools (Claude, Copilot, etc.) as a development partner, with the technical depth to steer them effectively in unfamiliar or complex codebases - Strong debugging instincts and the ability to move fast under pressure without cutting corners on security or quality - CI/CD pipeline ownership experience, including gating deploys on tests, coverage, and security scans ## Nice to Have Experience with mobile platforms (iOS/Android). Familiarity with FedRAMP, SOC 2, or other compliance frameworks that map to NIST. Experience with data warehousing or BI tooling. Container or serverless packaging experience. A CS degree or equivalent depth in fundamentals — data structures, concurrency, systems — however you came by it.

We are looking for an experienced API Integration Engineer to help finalize and optimize integrations for our security platform. The ideal candidate will have strong experience working with third-party APIs, authentication mechanisms, cloud-based AI services, and troubleshooting production integrations. Your primary responsibility will be to validate and configure API credentials for URL classification and IP reputation services, identify and integrate the correct Large Language Model (LLM) endpoint (OpenAI, Claude, Azure OpenAI, or custom/internal models), and ensure the overall system is secure, reliable, and high performing. This is a short-term contract with the potential for ongoing work if the engagement is successful. Responsibilities 1. Verify and configure API credentials for: - URL Classification services - IP Reputation services - Threat Intelligence APIs 2. Validate authentication methods including: - API Keys - OAuth 2.0 - Bearer Tokens - JWT 3. Identify the correct LLM provider and endpoint, including: - OpenAI - Claude (Anthropic) - Azure OpenAI - Google Gemini - Internal/custom LLM deployments 4. Confirm that all required API keys, secrets, and access tokens are correctly configured. 5. Test API connectivity and verify successful authentication. 6. Troubleshoot integration issues across development and production environments. 7. Optimize API performance, latency, retry mechanisms, and error handling. 8. Collaborate closely with our development team to resolve integration challenges. 9. Document the configuration process and provide recommendations for future maintenance. 10. Ensure best practices for credential management and secure secret storage. Required Skills 1. Strong experience integrating REST APIs 2. Experience with authentication protocols: - API Keys - OAuth2 - JWT - Bearer Tokens 3. Experience working with AI APIs including one or more of: - OpenAI - Anthropic Claude - Azure OpenAI - Google Gemini 4. Familiarity with URL reputation and threat intelligence services 5. Experience integrating IP reputation APIs 6. Strong debugging and troubleshooting skills 7. Knowledge of HTTP/HTTPS, JSON, webhooks, and API testing tools (Postman, Insomnia, etc.) 8. Experience with Python, Node.js, or similar backend technologies 9. Familiarity with cloud environments (AWS, Azure, or GCP) To Apply Please include the following in your proposal: - Brief overview of your experience with API integrations. - Examples of projects involving OpenAI, Claude, Azure OpenAI, or other LLM integrations. - Experience integrating URL classification, IP reputation, or cybersecurity APIs. - Your preferred development stack. We are looking for a highly skilled engineer who can quickly identify integration issues, ensure secure API connectivity, and help us deliver a robust, production-ready solution. If you have strong experience with API authentication, AI integrations, and troubleshooting complex systems, we'd love to hear from you.

Senior Fractional SaaS / Full-Stack Engineer for Production CRM Platform I am looking for an experienced Senior Full-Stack SaaS Engineer / Platform Engineer to provide independent technical oversight, production troubleshooting, architecture review, automated testing, and long-term engineering support for an existing construction-industry CRM platform called ForgeOne CRM. This is not a project to build a new application from scratch. ForgeOne is already a substantial working SaaS application with multiple modules, user roles, business workflows, customer/job management functionality, integrations, mobile and desktop interfaces, and an expanding feature set. The platform has been developed rapidly with significant use of modern AI-assisted development tools. That has allowed us to move very quickly, but the application is now reaching the point where I want an experienced senior engineer involved to help transition the development process from rapid feature-building into a more mature production environment with stronger automated testing, monitoring, release controls, architecture oversight, and regression prevention. I am the founder/business owner, not a traditional software engineer. I need someone who can understand the technical side deeply while also communicating clearly with me in normal business language. This will initially be a fractional/part-time position, approximately 5–10 hours per week depending on what is happening. If the relationship is successful and ForgeOne continues growing, this could potentially develop into a much larger role or eventually a full-time technical leadership/engineering position. What I Need My biggest priority is production reliability. As ForgeOne has grown, there are now enough interconnected features that making a change in one area can potentially create an unexpected issue somewhere else. I do not want to rely solely on the founder, employees, customers, or subcontractors manually discovering regressions after a release. I want to develop a proper engineering safety net around the platform. The person I hire should be capable of looking at the entire application as a system rather than only working on individual frontend tickets. You should be comfortable investigating problems across: * Frontend * Backend * APIs * Database * Authentication * User permissions * Multi-tenant data separation * Third-party integrations * Browser/mobile behavior * Deployment * Logging * Monitoring * Automated testing * Production infrastructure * Security Initial Assignment — Production Readiness / Architecture Audit The first thing I want is an independent technical review of the existing ForgeOne platform. I want someone experienced to examine how the system is currently structured before making major recommendations or changes. The review should include areas such as: * Overall SaaS architecture * Code organization and maintainability * Frontend/backend interaction * Database design * Multi-tenant architecture * Company/tenant data isolation * Authentication * Authorization and role-based permissions * API design * Third-party API integrations * Error handling * Logging * Production monitoring * Security * Secrets/environment configuration * Deployment process * Database migrations * Backup/recovery considerations * Performance * Scalability * Mobile responsiveness * Automated testing coverage * Release/change-management process * Technical debt that creates actual business risk I would like findings categorized approximately as: Critical — immediate production, security, data, or operational risk. High — should be corrected before significant customer growth. Medium — important improvements that should be placed on the engineering roadmap. Low — optimization, cleanup, or longer-term technical improvements. I also want the engineer to identify what is currently working well. I am not looking for someone who automatically recommends rebuilding everything because they prefer another framework or architecture. If part of the existing application works correctly, is secure, scalable enough for our requirements, and can be maintained, I want that taken into consideration. Changes should be driven by actual technical or business reasons. Automated Regression Testing A major project I want implemented is a comprehensive automated testing system that acts like real ForgeOne users. The goal is to automatically test critical workflows after changes instead of waiting for a human user to discover that something stopped working. I am interested in browser-based end-to-end testing using Playwright or an equivalent framework. Examples of workflows that should eventually be automatically tested include: * User login * New-user invitations * Invitation acceptance * Authentication * User permissions * Company/tenant separation * Dashboard loading * Navigation * Creating jobs * Opening existing jobs * Editing job information * Estimates * Saving information and returning to it * File uploads * Photo uploads * Multiple-file uploads * Customer workflows * Employee workflows * Subcontractor workflows * Notifications * Status/workflow changes * Mobile navigation * Desktop navigation * Responsive layouts * Major CRM modules * Third-party integration screens * Error states * Permission restrictions I want a structured test environment/test company using controlled test data rather than automated testing that performs destructive actions against real customer information. External integrations that could create real financial or operational transactions must be handled appropriately through sandbox environments, mocks, test accounts, or other safeguards. Production Monitoring I also want much stronger visibility into what is happening when something fails. I am interested in implementing or improving tools such as: * Sentry or equivalent application monitoring * Frontend error reporting * Backend error reporting * API failure tracking * Performance monitoring * Browser console error capture * Failed network request capture * Deployment/version tracking * Useful diagnostic logs * Screenshots or traces from failed automated tests When an automated test fails, I want enough information available that an engineer can quickly determine what happened rather than spending hours trying to reproduce an unknown problem. AI Reliability / Diagnostic Agent Another area I am interested in developing is an internal AI Reliability Agent. The AI should NOT have unrestricted authority to modify production code, production databases, or customer information. The primary purpose would be: * Monitoring * Testing * Diagnosing * Comparing failures with recent changes * Organizing logs * Identifying possible causes * Generating incident summaries * Helping prioritize issues * Suggesting possible fixes * Assisting engineers with investigation For example, if an automated browser test fails while opening a job, the ideal system could collect information such as: * Which test failed * Expected behavior * Actual behavior * Screenshot * Browser console errors * Network/API failures * Relevant application logs * Deployment/version * Recently modified files * Potential source of regression The AI could then help analyze that information and provide an engineer with a useful starting point. I want AI helping engineering, not AI operating production without appropriate controls. Experience with the OpenAI API, AI agents, LLM integrations, developer tooling, or AI-assisted diagnostics is valuable, but strong traditional software engineering experience is more important to me than someone whose primary background is prompt engineering. Release Process I want help developing a safer release process. The eventual goal is something similar to: Development/change → automated tests → code/technical review → staging/testing → approval → production deployment → production smoke tests → monitoring Critical workflows should be tested before a release is considered successful. I also want guidance on sensible rollback procedures when a production change creates a regression. Third-Party Integrations ForgeOne includes and is developing multiple third-party integrations. The engineer should be comfortable reviewing and troubleshooting: * REST APIs * OAuth/authentication flows * Webhooks * API credentials * Rate limits * Error handling * Retries * Sandbox versus production environments * Integration security * Data synchronization * Failure recovery Some integrations involve construction-industry suppliers and other outside service providers, so protecting credentials and preventing unintended external transactions is extremely important. Additional details regarding integrations and architecture can be provided to qualified candidates after appropriate confidentiality protections are in place. Security / Multi-Tenant SaaS Experience Multi-tenant security is extremely important. ForgeOne supports multiple independent companies using the same SaaS platform. I need someone who understands that authentication alone is not sufficient. The architecture must ensure that one customer/company cannot access another company’s: * Jobs * Customers * Employees * Financial information * Files * Photos * Communications * Credentials * Integration information * Other tenant-specific data Experience reviewing authorization, RBAC, tenant isolation, database access controls, API authorization, and SaaS security is highly desirable. Who I Am Looking For I am looking for a senior engineer who has actually supported real production SaaS applications. Ideal experience includes several of the following: * Senior full-stack development * SaaS application architecture * Multi-tenant applications * Modern JavaScript/TypeScript development * Modern frontend frameworks * Backend development * SQL/relational databases * API development * REST APIs * Authentication * Authorization * RBAC * Third-party integrations * Git/GitHub * CI/CD * GitHub Actions or equivalent * Playwright * Cypress or other automated E2E testing * Production monitoring * Sentry or equivalent * Cloud deployment * SaaS security * Performance troubleshooting * Production incident investigation * AI-assisted development * OpenAI/LLM integrations * AI agent development Experience with CRM, ERP, field-service, construction-management, project-management, fintech, insurance, or other workflow-heavy SaaS platforms is a strong plus. The exact technology stack and repository architecture can be discussed with shortlisted candidates rather than making assumptions in this posting. What I Am NOT Looking For I am not looking primarily for: * Desktop IT support * Help desk support * Network administration * Basic website development * WordPress development * Landing-page development * Someone learning SaaS development for the first time * A prompt engineer with limited traditional software engineering experience * An agency sending a salesperson while an unknown developer actually performs the work * Someone who immediately wants to rebuild the entire application before understanding it I want to communicate directly with the engineer who will actually be reviewing and working on ForgeOne. Working Style I move quickly and appreciate clear communication. I do not need technical terminology used simply for the sake of sounding technical. When there is a problem, I want an engineer capable of explaining: 1. What is wrong. 2. Why it matters. 3. What caused it or what likely caused it. 4. What options we have. 5. What they recommend. 6. What could potentially be affected by the change. 7. How we test the fix. 8. How we prevent the same problem from happening again. I value engineers who understand that the objective is not merely to make a bug disappear. The objective is to make the product more reliable after every fix. Engagement This will begin as an hourly fractional engagement. Expected initial involvement is approximately 5–10 hours per week, although hours may increase or decrease depending on the project phase. The first major deliverable will be the technical/production-readiness assessment. If that goes well, I would like the relationship to continue into: * Production stabilization * Automated regression testing * Monitoring * Release-process improvements * Architecture oversight * Security improvements * Integration review * Difficult production debugging * AI Reliability Agent development * Ongoing engineering consultation For the right person, this could become a significant long-term role as ForgeOne grows and could potentially transition into a full-time position in the future. When Applying Please do not send a generic copy-and-paste proposal. Please answer the following: 1. Describe a production SaaS application you personally worked on and what your responsibility was. 2. Have you taken over or audited an application that was developed rapidly and needed stabilization? What did you find and what did you do? 3. Describe your experience with multi-tenant SaaS applications and tenant data isolation. 4. What experience do you have with authentication, authorization, and RBAC? 5. What automated end-to-end testing tools have you used? 6. Specifically, what experience do you have with Playwright, Cypress, or similar browser automation? 7. What production monitoring/error-tracking systems have you implemented? 8. What is your experience troubleshooting difficult production regressions? 9. Have you worked with applications developed using AI-assisted coding tools? 10. Have you built AI agents or LLM-powered engineering/operations tools? If yes, briefly explain what they did. 11. If you discovered that an existing part of ForgeOne was designed differently than you personally would have designed it, how would you determine whether to leave it alone, improve it, or replace it? 12. Are you comfortable beginning with a paid technical audit before assuming broader responsibility? Please begin your proposal with “ForgeOne Review” so I know you read the posting. I am looking for an experienced engineer who can become a trusted independent technical resource for ForgeOne—not simply someone to complete isolated coding tickets.

UX Content Designer + Conversational AI Writer Contract / Freelance | Fintech + AI We’re looking for an experienced UX Content Designer + Conversational AI Writer to help shape the voice and member experience of Money Momma™ and bring Chip™, our AI financial support pup, fully to life. You must have experience working on shipped mobile or digital app products and collaborating directly with product designers, product managers, developers, and other cross-functional partners. This is not a marketing copywriting role. We already have a strong foundation for Chip’s personality, voice, tone, interaction style, and character guidelines. We need someone who can take that foundation further, pressure-test it, identify gaps and edge cases, and help turn it into a scalable conversational experience that works inside a real product. The Big Idea Money Momma is the brains behind the experience. It is the app, financial data, calculations, forecasts, and coaching logic. Chip is the relationship. Members can talk directly with Chip inside the app. He gets to know them, remembers context, celebrates their wins, helps when they’re stressed, explains what their numbers mean, and guides them through their financial journey. We want Chip to feel less like an AI assistant and more like your best financial support pup, a trusted friend who’s always in your corner. We need someone who understands how to design that relationship through language and how to make it work within the UX of an actual app. What You’ll Do Expand our existing Chip voice, personality, tone, humor, and interaction guidelines Design how Chip engages with members and builds a relationship over time Write natural conversations, responses, prompts, follow-up questions, and conversational CTAs Design interactions for wins, stress, confusion, setbacks, resistance, financial education, and sensitive moments Think through conversation flows, alternate responses, edge cases, dead ends, recovery, and out-of-scope situations Help define how context and memory make Chip’s interactions feel personal Identify gaps and potential problems in our existing conversational experience Expand our existing Chip Conversation Library and evolve AI writing guidelines for consistent implementation Write UX content across Money Momma, including onboarding, buttons, empty states, errors, tooltips, education, confirmations, and in-app messaging Write push notifications, emails, re-engagement messages, milestones, celebrations, and other member communications Help define when Money Momma speaks versus when Chip speaks Work directly with Product Design to ensure content and interaction design are developed together Collaborate with Product and Engineering to understand technical constraints and translate conversation designs into buildable experiences Review implemented experiences and help refine the content based on testing, product behavior, and member feedback Required Experience Professional UX writing or content design experience for mobile or digital apps Conversational AI, conversation design, chatbot, or AI assistant experience Experience working directly with product designers and developers Experience taking content from early UX flows or Figma designs through development and implementation Understanding of user flows, interaction states, errors, edge cases, and product logic Ability to write short, natural, personality-driven product copy Ability to work within an established voice while also challenging and improving it Experience with LLM products, fintech, financial wellness, consumer subscription apps, behavioral design, or character-driven experiences is a plus. What We Want to See Please do not send only marketing, advertising, social media, or website copy. We want to see actual product work. Please include 2 to 3 relevant case studies or working examples showing: The app or digital product you worked on The problem you were solving Your specific role and what you personally wrote or designed Examples of the actual UX or conversational experience How you collaborated with product designers How you worked with developers or engineering How your content changed based on UX, technical constraints, testing, or user feedback What ultimately shipped If you have worked on an AI assistant, chatbot, conversational character, or LLM-powered product, please show us the actual interaction design or conversation examples whenever possible. We’d also like to hear how you would approach taking an existing character personality and voice, like Chip, and turning it into a conversational system that can scale across an app. Freelance/contract role with potential for ongoing work.

We are seeking a hands-on UX Designer to improve messaging experiences across mobile applications and desktop web products serving multiple user groups. This role will design new AI-powered messaging features and improve communication patterns so users can respond more effectively, understand conversation status, and re-engage when appropriate. The ideal candidate has strong end-to-end product design experience, a portfolio demonstrating complex product workflows, and the ability to work independently within an established product environment. Enterprise experience strongly preferred. Key Responsibilities * Design end-to-end product experiences across mobile applications and desktop web. * Create wireframes, user journeys, interactive prototypes, and high-fidelity mockups. * Design user experiences for AI-powered messaging features. * Improve communication responsiveness through reply prompts, expectation setting, status transparency, and re-engagement patterns. * Simplify complex workflows and data-heavy experiences involving search, filtering, data export, or similar functionality. * Apply established design-system components, patterns, and visual standards. * Collaborate with Product Management, Engineering, UX Research, and Legal partners. * Incorporate qualitative research findings and user feedback into design iterations. * Support design validation through qualitative research and A/B testing. * Prepare clear design specifications and handoff materials for engineering teams. * Work independently, manage assigned design work, and ramp quickly with minimal oversight. Must-Have Skills * 3+ years of professional product UX design experience. * Portfolio demonstrating end-to-end product UX work. * Strong interaction design, visual design, prototyping, and user-journey design skills. * Experience designing complex workflows or data-heavy enterprise product experiences. * Experience with search, filtering, data export, or comparable complex interaction patterns. * Ability to work independently and operate effectively with minimal oversight. * Experience collaborating with Product, Engineering, Research, and Legal stakeholders. * Experience incorporating UX research findings and user feedback into product designs. * Strong written and verbal communication skills. * Recent hands-on individual contributor experience. Nice-to-Have Skills * Experience designing messaging, inbox, communications, or notification products. * Accessibility expertise, including familiarity with WCAG and assistive technologies. * Experience designing international or localized products. * Experience designing products for the Japanese market. * Mobile-first product design experience. * Experience supporting A/B testing or experimentation programs. * Prior contractor or embedded-team experience within a large product organization. * Experience designing AI-enabled product features. Required Tools & Platforms * Strong, current Figma proficiency. * Experience creating interactive prototypes. * Experience with design-to-engineering handoff workflows. * Experience working within an established design system. Location, Time & Engagement * Remote contract opportunity. * Candidates must be located in the United States. * Must be available for full-time work at 40 hours per week. * Must be able to work with teams operating in the U.S. Central time zone. * Contract is expected to continue through March 31, 2027.

# AI Business Tools Trainer and Consultant for Healthcare/DME Company ## Project Overview Hiro Health is a growing healthcare company specializing in sleep diagnostics, CPAP therapy, PAP resupply, oxygen services, ventilator services, and durable medical equipment. We are seeking an experienced AI business trainer and consultant to provide personalized, hands-on instruction to the company owner and selected managers. The goal is to teach us how to effectively use AI platforms such as: * ChatGPT * Claude * Google Gemini * Microsoft Copilot * Other relevant AI and automation tools This is not a general introductory AI course. Training must be customized around Hiro Health’s actual business operations, financial reporting, healthcare research, management responsibilities, and growth plans. ## Primary Objective At the completion of the project, we should be able to independently use AI to: * Analyze business and financial information * Improve operational processes * create reports, policies, and procedures * Conduct reliable business and healthcare research * Develop employee and management materials * Evaluate acquisitions and growth opportunities * Identify tasks that can be automated * Select the best AI platform for each type of project * Protect confidential patient, employee, and company information The consultant should teach us how to use AI—not simply perform the work on our behalf. ## Areas of Training ### 1. AI Platform Selection Teach us the differences between ChatGPT, Claude, Gemini, and Microsoft Copilot, including: * Strengths and weaknesses of each platform * Best business uses for each tool * Free, paid, business, and enterprise account differences * File-upload and data-analysis capabilities * Research and source-verification capabilities * Integration with Microsoft 365, Google Workspace, and other systems * Privacy and data-retention considerations ### 2. Prompt Development Teach us how to: * Write clear and effective prompts * Provide the appropriate background, data, and instructions * Improve an AI-generated answer through follow-up prompts * Create reusable prompt templates * Build multi-step prompts for complex projects * Reduce inaccurate or fabricated responses * Verify important facts and calculations * Convert successful prompts into standardized company workflows ### 3. Financial Analysis Use realistic Hiro Health examples to teach AI-assisted: * Profit-and-loss statement analysis * Balance-sheet and cash-flow analysis * Budget development * Financial forecasting * Gross-margin analysis by service line * Labor and productivity analysis * KPI development and reporting * 13-week cash-flow forecasting * Acquisition valuation and financial modeling * SBA loan and debt-service analysis * Excel formula, table, dashboard, and chart creation * Comparison of actual results against budgets and benchmarks ### 4. Operations and Process Improvement Teach us how to use AI to: * Create and improve standard operating procedures * Document departmental workflows * Identify process bottlenecks * Develop quality-control checklists * Build employee training materials * Analyze operational reports * Create management dashboards * Develop implementation and project plans * Improve CPAP setup, resupply, sleep-testing, oxygen, and ventilator workflows * Identify repetitive tasks that may be automated ### 5. Sales and Referral Management Training should include: * Physician-referral data analysis * Referral-source ranking and segmentation * Sales-territory analysis * Identification of declining or underperforming accounts * Sales representative performance analysis * Sales plans and account strategies * Physician outreach emails and materials * Competitor and market research * Commission and incentive-plan modeling * Customer-review and satisfaction analysis ### 6. Human Resources and Management Teach us how to use AI to develop: * Job descriptions * Interview questions * Candidate scorecards * Performance evaluations * Employee policies * Corrective-action plans * Training documents * Internal company communications * Meeting agendas and summaries * Organizational and staffing plans * Compensation comparisons * Employee productivity measurements ### 7. Healthcare, DME, and Reimbursement Research Teach us how to conduct and verify research involving: * Medicare and commercial insurance requirements * DME billing and reimbursement * HCPCS and CPT codes * CPAP, oxygen, ventilator, and sleep-testing requirements * Industry benchmarks * Market and competitor information * Accreditation and licensing requirements * New product and service opportunities * Authoritative government and payer sources The trainer should emphasize that AI research does not replace legal, clinical, billing, compliance, or accounting review. ### 8. AI Automation Opportunities Teach us how to identify and evaluate opportunities involving: * Microsoft Copilot * Microsoft Power Automate * AI agents * Robotic process automation * Scheduled reports * Automated document summaries * Email and meeting follow-up * Data extraction and classification * Management notifications * Brightree, QuickBooks, Microsoft Fabric, Shopify, and Microsoft 365 workflows The consultant should explain when generative AI is appropriate and when traditional automation or systems integration is a better solution. ## Healthcare Privacy and Security Because Hiro Health operates in healthcare, the training must address: * HIPAA and protected health information * Personally identifiable information * De-identifying information before using AI * Consumer versus enterprise AI accounts * Business Associate Agreement requirements * Data-retention and model-training settings * User access and permission controls * Approved and prohibited AI uses * Review requirements before AI-generated work is used * Situations in which information should never be entered into an AI platform Actual patient information should not be used during training. Examples should rely on synthetic, anonymized, or properly de-identified information. ## Preferred Project Structure We anticipate a six-to-eight-week engagement consisting of: * One or two virtual training sessions per week * Approximately 60–90 minutes per session * Hands-on exercises using Hiro Health business scenarios * Assignments between sessions * Recordings of sessions when permitted * Reusable templates and reference materials * Limited follow-up support between sessions * A final AI implementation plan We are open to an alternative structure if the consultant recommends a more effective approach. ## Required Deliverables The consultant should provide: 1. An initial assessment of our AI knowledge and business priorities. 2. A customized training curriculum. 3. Live, hands-on training sessions. 4. A comparison guide for ChatGPT, Claude, Gemini, and Microsoft Copilot. 5. A reusable prompt library organized by business function. 6. At least five completed AI-assisted workflows based on Hiro Health’s needs. 7. Step-by-step instructions for each workflow. 8. An AI privacy, security, and acceptable-use checklist. 9. A process for verifying AI-generated work. 10. Recommendations for appropriate business or enterprise AI subscriptions. 11. A prioritized list of future automation opportunities. 12. A 90-day AI implementation roadmap. ## Ideal Candidate The ideal consultant will have: * Advanced experience with ChatGPT, Claude, Gemini, and Microsoft Copilot * Experience teaching business owners and executives * Strong prompt-engineering and workflow-design skills * Experience with Excel and Microsoft 365 * Business financial-analysis experience * Knowledge of AI privacy, security, and governance * The ability to explain technical topics in straightforward business language * Experience converting AI use cases into repeatable company processes Healthcare, DME, HIPAA, Brightree, QuickBooks, Microsoft Fabric, or Power Automate experience is strongly preferred. ## Proposal Requirements Please include: * A summary of your relevant experience * Examples of similar AI training engagements * Your experience with healthcare or regulated businesses * Your proposed training structure * Estimated project timeline * Hourly rate or fixed project price * Examples of training materials or workflows you have created * Relevant AI, Microsoft, healthcare, or technology certifications * Your availability for live virtual sessions ## Applicant Screening Questions 1. How would you compare ChatGPT, Claude, Gemini, and Microsoft Copilot for a healthcare business? 2. What precautions should a HIPAA-regulated company take when using AI? 3. Describe a business workflow you have improved using generative AI. 4. How do you teach users to recognize incorrect or fabricated AI answers? 5. How would you structure a customized AI training program for Hiro Health? 6. What experience do you have using AI with Excel, financial statements, and operational data? 7. How would you help us build a reusable company prompt library? 8. What healthcare, DME, Microsoft 365, or automation experience do you have? ## Definition of Project Success At the conclusion of the project, Hiro Health’s owner and participating managers should be able to: * Select the appropriate AI tool for a specific business need * Write effective prompts without outside assistance * Analyze common company reports and spreadsheets * Create professional business documents * Conduct and verify business research * Protect confidential and regulated information * Develop reusable prompts and AI workflows * Identify strong candidates for automation * Train additional employees on approved AI practices * Continue developing AI-assisted workflows independently

I'm the author of a practical nonfiction book on using AI effectively, drawing on 60 years of software engineering methodology. It's written for a general professional audience — not developers — who want a real framework for working with AI instead of just "prompting harder." Self-publishing on Amazon KDP (ebook + paperback); I'm handling the upload myself and looking for help with promotion around launch. Scope of work: 1. Social media promotion — create and post content to build visibility before and after launch. Open to your recommendation on which platforms make sense for this audience (LinkedIn, X, relevant subreddits, etc. — please propose a platform strategy in your application rather than assuming Instagram/TikTok). 2. Reviewer/podcast/newsletter outreach — research and pitch book bloggers, podcast hosts, and AI/productivity-focused newsletters for reviews, features, or interview opportunities. This is NOT included / not wanted: - No paid ad management (Amazon Ads is being handled separately) - No review-purchasing, review-swap, or any review-manipulation services Timeline: ~4-6 weeks covering pre-launch and launch window. Budget: Fixed price (open to discussing based on your proposed plan — please quote against a specific deliverable list, not an hourly open-ended retainer). To apply, please include: - Examples of past book launches or author-platform work you've done (links if possible) - Your proposed platform/outlet strategy for this specific book (a few sentences is enough) - Whether you're proposing this as a single fixed-price project or would want a short paid trial first

We are seeking an experienced, analytical, collaborative, and self-driven **Implementation Consultant** to lead successful customer implementations and help clients translate their sales strategy, technology, and AI initiatives into scalable, executable workflows. This role sits at the intersection of **sales strategy, sales technology, AI, implementation, enablement, and project management**. You will work directly with clients to understand their business goals, sales processes, technology stack, outbound strategy, and AI use cases, then translate those requirements into effective systems, workflows, and processes. You will own implementations from kickoff through launch and adoption, ensuring each client has the technology, processes, AI workflows, enablement, and operating cadence required to achieve measurable results. The ideal candidate understands how high-performing sales organizations operate, has strong experience with **Outreach**, and is comfortable working hands-on with modern AI platforms such as **ChatGPT/GPT, Claude, and Gemini**. You should understand prompt engineering, how to build repeatable AI workflows, and how to translate business requirements into scalable AI-enabled processes. This position reports to the **Implementation Manager**. ## What You’ll Do ### Own Customer Implementations * Lead end-to-end customer implementations from kickoff through launch, adoption, and transition. * Serve as the primary implementation partner and trusted advisor for assigned clients. * Manage multiple client implementations simultaneously while maintaining clear timelines, deliverables, and communication. * Translate customer goals and business requirements into actionable implementation strategies. * Establish clear expectations, milestones, responsibilities, and success criteria at the beginning of each engagement. * Help create a predictable, repeatable, and scalable implementation methodology. ### Understand the Customer’s Sales Motion * Develop a deep understanding of each customer’s business, sales organization, target market, outbound strategy, technology stack, and performance goals. * Evaluate existing sales processes, workflows, messaging, technology utilization, and performance measurement. * Conduct discovery sessions, needs assessments, and gap analyses to identify opportunities for improvement. * Understand the customer's value proposition, personas, segmentation strategy, sales process, messaging framework, and value-based selling methodology. * Identify opportunities to improve the effectiveness, scalability, and efficiency of the customer’s outbound motion. ### Outreach Implementation & Optimization * Configure, implement, and optimize **Outreach** based on customer requirements and sales strategy. * Build and optimize sequences, workflows, triggers, tasks, rulesets, templates, snippets, user settings, governance, and administrative configurations. * Help customers establish scalable Outreach processes and platform best practices. * Evaluate how Outreach integrates into the customer's broader CRM and sales technology ecosystem. * Identify opportunities to automate repetitive workflows and improve seller productivity. * Conduct testing and quality assurance to ensure configurations function as designed. * Advise administrators and sales leaders on Outreach adoption, governance, reporting, and ongoing optimization. ### AI Prompting & Workflow Development * Design, test, and refine AI prompts that support sales, prospecting, research, personalization, messaging, enablement, and operational workflows. * Build reusable prompt frameworks that generate consistent, high-quality outputs at scale. * Work hands-on with AI platforms including **OpenAI / ChatGPT / GPT models, Claude, and Gemini**. * Translate business requirements and sales methodologies into structured AI instructions and workflows. * Develop AI-powered processes for use cases such as: * Account and prospect research * Email personalization * Persona-based messaging * Value proposition development * Call preparation * Objection handling * Sequence creation * Lead and account prioritization * Data enrichment and summarization * Sales coaching and enablement * Build multi-step AI workflows that combine data, prompts, business logic, and sales technology. * Create prompts with clear context, inputs, instructions, guardrails, formatting requirements, and output criteria. * Test AI outputs for accuracy, relevance, consistency, tone, and usability. * Diagnose poor AI outputs and improve prompts, context, logic, or workflow structure accordingly. * Help customers understand when AI should augment a workflow versus when traditional automation or human judgment is more appropriate. * Develop scalable AI workflows that can be consistently adopted across teams rather than relying on one-off prompting. * Stay current on emerging AI capabilities and identify practical applications within sales and revenue workflows. ### AI Strategy & Enablement * Help customers identify high-value opportunities to incorporate AI into their sales processes. * Assess existing AI usage and identify gaps, inefficiencies, and opportunities for automation. * Consult customers on responsible and effective use of generative AI within their organization. * Develop prompting standards, AI workflow documentation, and repeatable best practices. * Train customers on how to effectively use GPT, Claude, Gemini, and other AI tools in their daily workflows. * Teach users how to provide appropriate context, structure prompts, evaluate outputs, and iterate on AI-generated content. * Help customers move beyond individual AI usage toward standardized, operationalized AI workflows. ### Build the Implementation Strategy * Develop detailed implementation plans outlining project scope, timelines, milestones, owners, dependencies, and required resources. * Develop a clear strategic roadmap for the customer’s implementation and future-state sales motion. * Help customers establish an effective operating cadence for managing and optimizing outbound performance. * Identify implementation risks, blockers, and dependencies early and develop mitigation plans. * Ensure alignment between customer objectives, technology capabilities, AI workflows, and project scope. ### Develop Processes & Best Practices * Help clients design scalable outbound processes aligned with industry best practices. * Develop workflows and processes that improve seller productivity, consistency, personalization, and execution. * Advise customers on how best-in-class sales organizations structure outbound programs. * Evaluate how performance should be measured across activity, execution, conversion, adoption, and outcomes. * Establish repeatable processes that customers can maintain after implementation. * Capture measurable performance improvements and opportunities for continued optimization. ### Training & Enablement * Lead customer training sessions, workshops, and enablement programs. * Educate administrators, managers, and end users on Outreach, AI workflows, prompting, and implemented processes. * Develop documentation, prompt libraries, training materials, implementation guides, and best-practice resources. * Translate technical functionality and AI concepts into practical workflows that sales teams can easily understand and adopt. * Answer customer questions and provide strategic and tactical guidance throughout implementation. * Support customers in developing continued learning and adoption plans after launch. ### Change Management & Adoption * Help customers manage organizational and workflow changes resulting from new technology, processes, and AI adoption. * Develop adoption strategies, communication plans, and rollout recommendations. * Identify potential resistance, adoption risks, or process gaps and proactively address them. * Partner with customer leadership to drive accountability and adoption across sales teams. * Ensure customers are prepared to successfully operate and optimize their technology and AI workflows following implementation. ### Data, Systems & Integrations * Support data migration, configuration, and workflow implementation activities when required. * Coordinate the movement and utilization of data between sales systems. * Validate data quality, accuracy, and completeness throughout the implementation process. * Understand how CRM data, Outreach data, third-party data, and AI inputs work together within customer workflows. * Partner with technical resources on integrations, APIs, automations, and more complex technical requirements. * Identify data-related issues that could impact AI output quality, workflow effectiveness, or successful launch. ### Project Management * Own internal and external project management for assigned implementations. * Maintain project plans, timelines, action items, risks, dependencies, and decision logs. * Drive stakeholders toward deadlines and proactively escalate potential blockers. * Coordinate across internal teams to ensure implementations remain on track. * Communicate project status, risks, accomplishments, and next steps clearly to internal and external stakeholders. * Ensure implementation issues are documented, prioritized, and resolved quickly. ### Reporting & Continuous Improvement * Track implementation milestones, customer engagement, platform adoption, AI workflow adoption, and key performance indicators. * Capture pre- and post-implementation performance improvements where applicable. * Provide clear implementation progress updates and documentation. * Maintain accurate project records and customer communication. * Identify patterns and lessons learned across implementations. * Use implementation insights to improve processes, documentation, prompts, workflows, enablement, and customer experience. * Contribute to the continued development of implementation methodologies and best practices. ## What We’re Looking For * 2+ years of experience in implementation, customer onboarding, consulting, sales operations, revenue operations, sales enablement, or a similar client-facing role. * Hands-on experience managing multiple customer implementations or projects simultaneously, ideally **8+ active accounts or projects at a time**. * At least 1 year of hands-on experience with **Outreach**. * Strong working experience with generative AI platforms such as **ChatGPT, GPT models, Claude, and/or Gemini**. * Demonstrated experience writing, testing, and optimizing AI prompts. * Experience building repeatable AI workflows rather than relying solely on ad hoc AI prompting. * Ability to structure prompts using context, variables, business rules, examples, constraints, and defined output formats. * Understanding of how AI can be applied to sales prospecting, personalization, messaging, research, coaching, and sales operations. * Experience working within a B2B technology, SaaS, sales technology, or revenue technology organization. * Strong understanding of how high-performing companies build and execute outbound sales strategies. * Understanding of sales engagement platforms, sequencing, workflows, personas, account segmentation, messaging, and sales process design. * Ability to translate business objectives into technical configurations, AI prompts, and executable workflows. * Strong project management and organizational skills. * Strong customer-facing communication, presentation, and facilitation skills. * Ability to build credibility with sales leaders, administrators, RevOps teams, and frontline sellers. * Ability to balance strategic thinking with detailed tactical execution. * Strong analytical and problem-solving skills. * Intellectual curiosity and the ability to quickly learn new AI tools, technologies, and workflows. * Ability to independently manage priorities, deadlines, stakeholders, and competing projects. * Comfortable operating in a fast-paced, continually evolving environment. ## Preferred Qualifications * Previous experience in a quota-carrying sales, SDR, BDR, sales management, sales enablement, or RevOps role. * Experience designing or managing outbound sales programs. * Experience implementing or administering Outreach. * **Outreach Administrator Certification strongly preferred.** * Experience building AI-powered sales or revenue workflows. * Experience creating sophisticated prompt libraries or GPT-based workflows for business users. * Experience working across multiple LLMs, including OpenAI, Anthropic Claude, and Google Gemini. * Familiarity with APIs, webhooks, automation platforms, structured data, or no-code/low-code workflow tools is a plus. * Experience consulting with clients on sales process, sales technology, AI, or revenue operations. * Experience with CRM and adjacent sales technology platforms. * Bachelor’s degree preferred. ## What Success Looks Like A successful Implementation Consultant will: * Consistently launch customer implementations on time and within scope. * Create a seamless and highly consultative customer experience. * Build strong relationships and credibility with customer stakeholders. * Translate outbound strategy into practical Outreach configurations, processes, and workflows. * Build AI prompts and workflows that produce reliable, scalable, high-quality outputs. * Help customers operationalize AI rather than simply experiment with it. * Drive strong customer adoption of Outreach, AI workflows, and newly implemented processes. * Identify risks before they become implementation blockers. * Demonstrate measurable improvements in customer execution, productivity, and performance. * Continuously improve implementation methodologies, AI prompts, documentation, and best practices. * Help create a scalable, predictable, and repeatable implementation motion.

Fractional Forward-Deployed Finance Lead QuantFi builds a strategic finance platform for CFOs: dashboards, reporting and scenario tools, unit economics, and cost analytics. We deploy it into each client's environment and run it under a monthly managed service. The company was founded by two finance operators and works with venture-backed and PE-backed companies. The role: Each engagement is run by a two-person pod: a finance lead (this role) paired with a full-stack AI engineer, with fractional security support behind them. The engineer owns the code. The finance lead owns the client relationship and the quality of everything the client sees. Responsibilities: -Run the client relationship: weekly meetings with the CFO, translate their priorities into a build plan, keep them updated in writing. -Own data quality: reconciliations, metric definitions, clean mappings from source systems. Dashboards ship when the numbers tie. -Direct the engineer's work: set priorities, review output, decide what goes in front of the client. -Run the engagement like a project: keep a live view of open workflows and priorities, and make it clear at all times what is in whose court (client, engineer, or offshore execution team). -Manage onboarding: gather requirements and system access in one organized request rather than a stream of asks. Identify expansion opportunities: cost discrepancies, pricing issues, reporting work the client's team is still doing manually. Qualifications -Strategic finance background: FP&A, banking, consulting, or fractional CFO work. Real experience with close cycles, board reporting, and budget vs. actuals. -Accounting fluency: able to answer client questions on accounting policy on the spot. Clean accounting is table stakes on every engagement, and the finance lead is the client's point of contact for it even when execution sits with an offshore controller team. -Comfortable presenting to CFOs and senior finance leadership. -Strong with spreadsheets and financial systems (QuickBooks or similar); SQL a plus. Uses AI tools regularly and can explain any output they present. -Organized: agendas, action items, written status updates without prompting. -Industry depth in CPG, SaaS, consumer, or PE-backed businesses is a strong plus; engagements are matched to sector expertise where possible. Structure and compensation: Independent contractor. Roughly 10-20 hours per week per engagement to start, with a path to full time as engagements grow. Hourly rate $100-150 plus a discretionary success fee based on how independently the engagement runs. Strong performers earn additional engagements and rate increases; rate progression is tied to demonstrated ability to own client communications end-to-end and delegate execution effectively. Your schedule is your own outside of client meetings; other clients are fine, but this role is built for dedicated independent fractional operators rather than a side project alongside a full-time job. US-based or US-hours preferred. Process: 1. Intro conversation, including a walk through a P&L you know well 2. Review of a sample dashboard: what's wrong with it, what a CFO would question 3. Short mock client check-in 4. Paid trial on a scoped, isolated opportunity — we move quickly on fit decisions in both directions