We are looking for an experienced AI automation developer to build a private executive assistant named Jarvis for a business owner named Vince. Jarvis must operate as a professional, respectful, fast-moving executive assistant. The assistant will communicate with Vince through iMessage, access his Google Calendar, remember important information, send meeting reminders, and maintain local files/data on an office iMac. This is not a basic chatbot. We need a working AI assistant that can hold real conversations, remember context, anticipate needs, and protect Vince’s time. Core Requirements The assistant must: Communicate with Vince through iMessage on macOS. Store all data, memory, and files locally on the office iMac. Access Vince’s personal Google Calendar. Send Vince a message 20 minutes before meetings. Remember meeting times, preferences, important facts, and prior conversations. Use context from previous messages and stored memory. Start conversations professionally with: “Hello Sir. What do you need today sir.” Maintain a direct, respectful, professional tone. Avoid fluff, long explanations, repetition, and unnecessary questions. Understand that Vince has zero tolerance for wasted time. Validate Vince’s instructions and respond with useful answers quickly. Ask onboarding questions at first launch to learn Vince’s occupation, goals, priorities, communication preferences, daily routines, and assistant expectations. Be built in a way that can expand later into email, task management, document handling, and proactive reminders. Important Personality / Communication Rules Jarvis must be designed around Vince’s communication style: Direct. No fluff. No jargon. Lead with the answer. Never ask for information Vince has already provided. Protect his time, brand, relationships, and workflow. Jarvis should function as an executive personal assistant whose purpose is to remember everything so Vince does not have to repeat himself. Technical Scope The developer should be comfortable with: macOS automation. iMessage / Messages.app integration. Google Calendar API. Local file storage and local memory architecture. AI agent frameworks. Cron jobs or scheduler-based reminders. Secure credential handling. Local database or file-based memory. Python, Node.js, or similar automation stack. Optional: BlueBubbles, AppleScript, Shortcuts, SQLite, vector database, local LLM tools, OpenAI API, Claude API, or similar. There is already a macOS/iMessage path available using CLI-based message tooling, but we are open to the developer recommending the best reliable implementation. Existing iMessage automation concepts include sending, reading, and watching message history through macOS Messages.app tooling. Deliverables We need the developer to provide: Working Jarvis assistant installed on the office iMac. iMessage communication with Vince. Google Calendar integration. Automatic 20-minute meeting reminders by text. Local memory system. Local file/data storage structure. First-run onboarding question flow. Prompt/personality system for Jarvis. Basic admin documentation showing how to restart, update, and maintain the assistant. Security notes for credentials, permissions, and local storage. Testing checklist proving iMessage, memory, reminders, and calendar sync work. First-Run Intro Flow Jarvis should text Vince an introductory message and ask important setup questions such as: What is your primary occupation? What are your top business priorities right now? What meetings or events should I always remind you about? Who are your key contacts? What should I never interrupt you for? What should I always notify you about? What tone do you prefer from me? What daily reminders would make your life easier? What are your current goals for the next 30, 60, and 90 days? Ideal Candidate The ideal freelancer has built AI agents, personal assistants, calendar bots, local automation tools, or macOS/iMessage workflows before. We want someone practical who can build a reliable working system, not just create a demo. Please include: Similar AI assistant or automation projects you have built. Your recommended tech stack. How you would connect iMessage. How you would handle local memory. How you would secure calendar credentials. Estimated timeline. What you need from us to start.

Summary We are seeking a highly skilled Automation + AI Systems Specialist to help design, build, and refine workflows, automations, and AI-assisted operational systems for our growing recruiting and staffing company. We work in a fast-paced recruiting and talent acquisition environment where speed, organization, lead management, and operational efficiency are critical. As we continue to grow, we are looking for a long-term automation partner who can help us streamline operations, connect systems, reduce manual work, and build scalable infrastructure across departments. We are not looking for someone who only builds simple one-step automations. We already utilize automation across several parts of our company and are seeking an experienced expert who can help architect more sophisticated systems, troubleshoot complex workflows, recommend scalable solutions, and integrate AI meaningfully into our operations. PROJECT EXAMPLES: Build AI-assisted recruiting workflows for sourcing, screening, and candidate management Create automated intake and routing systems for candidates, clients, and internal recruiting teams Develop AI-powered workflows for resume formatting, candidate summaries, and job description generation Automate onboarding/offboarding workflows for clients, candidates, and internal staff Connect HubSpot, Salesforce, Jotform, and other systems to improve data consistency and reduce manual administrative work Build workflows that sync recruiting data between CRMs, forms, spreadsheets, email marketing systems, and project management tools Create automated reporting dashboards and recruiting performance visibility systems Help transition fragmented automations into cleaner, centralized systems Troubleshoot failed automations, broken workflows, API issues, and sync errors Build AI-assisted SOP/documentation workflows for recurring internal processes Improve lead management, pipeline tracking, and marketing automation workflows IDEAL CANDIDATE: Senior-level AI/Automation expert with experience building advanced multi-step workflows currently in production Strong understanding of operational systems and process optimization — not just technical implementation Experience integrating AI tools and LLMs into real business workflows using OpenAI, Claude, APIs, or agent-based systems Advanced experience with platforms like n8n, Zapier, Make, HubSpot Workflows, and API integrations Comfortable designing scalable systems that are reliable, maintainable, and well-documented Able to identify inefficiencies and proactively recommend better operational approaches Comfortable with light-to-moderate coding (JavaScript, Python, APIs, webhooks, etc.) Strong communicator who can collaborate with both technical and non-technical team members TOOLS WE CURRENTLY USE: HubSpot Salesforce Zapier n8n Jotform OpenAI / ChatGPT Anthropic / Claude Various recruiting, CRM, and project management platforms Open to recommendations for better infrastructure/tools as needed BONUS EXPERIENCE: Recruiting, staffing, or HR-tech industry experience CRM/data architecture AI knowledge management systems Lead routing and sales pipeline automations Dashboarding and reporting systems Experience scaling operational systems for growing companies This will likely begin with one or two high-priority projects and expand into an ongoing relationship as we continue scaling our systems and operations. If you have experience building sophisticated automation ecosystems and enjoy helping companies operate more intelligently and efficiently, we’d love to connect.

US-BASED CONTRACT FULL-STACK / AI ENGINEER FOR HEALTHCARE PRODUCT Remote, US-Based Contractor | East Coast Time Required | Home Health AI Product About Scribble Scribble is the top-rated AI platform for home health purpose-built to give clinicians their time back. Home health agencies run on documentation: visit notes, care plans, prior authorizations, compliance paperwork - we help automate these processes. Project Overview We are looking for one or more experienced US-based contractors to help us move faster across several important areas of our product. We need hands-on builders who can scope clearly defined product needs, ask the right questions, and independently deliver high-quality work. This is not a narrow ticket-taking role. We are looking for people who can own meaningful pieces of the product, communicate clearly, work asynchronously, and make steady progress without heavy day-to-day management. Depending on your strengths, the work may focus on mobile, backend, AI workflows, and EMR robotic process automation. You will ideally own end to end development including testing. What We Need Help With • Build and improve visit types and clinical documentation workflows for home health use cases • Improve accuracy of AI-generated outputs, including prompt design, evaluation, testing, and workflow refinements • Integrate completed visits and documentation into EMR systems using APIs where available and robotic process automation where needed • Work across React Native mobile app features, Node.js backend services, OpenAI/LLM workflows, and automated testing • Debug production issues, improve reliability, and help us ship quickly without sacrificing quality • Troubleshoot and fix bugs quickly, and make product improvements based on customer feedback • Translate product requirements into practical technical plans and independently execute against them • Document decisions, provide frequent updates, and proactively flag risks, blockers, and trade-offs • Potentially collaborate with team members across different parts of the roadmap Skills We Are Looking For Required • Advanced use of Claude Code • US-based contractor with East Coast time zone availability required • Strong experience with React Native mobile development • Backend experience with Node.js, APIs, databases, authentication, and production debugging • Hands-on experience with OpenAI or other LLM APIs, prompt engineering, structured outputs, and AI workflow testing • Strong testing mindset, including unit tests, integration tests, regression testing, and quality checks for AI outputs • Ability to work independently from a product goal, break it into technical tasks, and deliver without constant direction • Excellent written and verbal communication; concise updates, clear questions, and proactive status reporting are essential • Speed and quality are both must-haves: we need someone who can move quickly while still shipping reliable, well-tested work • Comfortable working with sensitive healthcare data and following HIPAA-aware, security-conscious development practices Strongly Preferred • Meaningful healthcare experience is strongly preferred, especially in home health, clinical documentation, EMR/EHR workflows, HIPAA-aware development, or regulated healthcare environments Contract Details • Contract role for a US-based independent contractor • US-based candidates only; East Coast time zone availability is required • Part-time or project-based to start, with potential for ongoing work • Minimum availability of 20 hours per week is required • We may hire multiple contractors based on specialty, fit, and availability • Clear deliverables, frequent communication, and fast iteration cycles • Hourly rate or fixed-price milestones can be discussed based on scope and experience • Selected contractors will need to sign appropriate IP assignment, NDA, and Business Associate Agreement documents before accessing sensitive product or healthcare data • We may request and check references before starting a larger engagement

I’m looking for an AI Engineer to help build an automated red-teaming product based on open-source models. This is a short-term, hands-on project for around 2 months, with an expected commitment of about 20 hours per week. The goal is to build a specialized red-teaming engine that can generate adversarial prompts across different risk domains, severity levels, and attack strategies — then automatically run those prompts against target AI models to identify bad cases, failure patterns, and safety gaps. 🔍 What you’ll work on Build red-teaming systems on top of open-source LLMs, including fine-tuning, prompt optimization, evaluation pipelines, and model orchestration. Design automated prompt generation workflows across risk domains such as self-harm, hate, violence, sexual safety, misinformation, fraud, cyber, and other high-risk areas. Generate prompts across different harm levels, from benign edge cases to policy-borderline and clearly unsafe scenarios, while maintaining structured taxonomies and evaluation criteria. Run automated tests against target models such as Gemma, Llama, Qwen, or other open-source / closed-source models to surface jailbreak patterns, over-refusal, under-refusal, and policy inconsistencies. Build feedback loops that turn model failures into stronger red-team prompts, improved eval sets, remediation recommendations, and continuous safety testing. 🧠 What I’m looking for Hands-on experience with open-source LLMs, fine-tuning, LoRA / QLoRA, RAG, model evaluation, and LLM inference pipelines. Familiarity with AI safety, red teaming, adversarial prompting, jailbreaks, safety evals, or trust & safety systems. Ability to build end-to-end systems, including data pipelines, model serving, eval harnesses, scoring, dashboards, and automation workflows. Bonus if you’ve worked on model safety, content moderation, policy evaluation, agentic testing, or automated eval infrastructure. ⏳ Project setup Duration: around 2 months Time commitment: about 20 hours per week Format: flexible / remote-friendly Stage: early-stage build, from 0 to 1 🚀 Why this is interesting This is not about manually writing red-team prompts one by one. The goal is to build a scalable system that can continuously generate, test, categorize, and learn from model failures — helping teams understand where AI models break, why they break, and how to improve them. If you enjoy working with open-source models, AI safety, red teaming, and fast 0-to-1 product building, I’d love to chat. Feel free to DM me if this sounds like you, or if you know someone who might be a good fit.

Aria Technology Solutions is not a traditional B2B tech agency. We don’t build other people’s dreams or fix legacy corporate code. We are a fast-moving, asymmetric Product Factory and Venture Studio. Utilizing advanced AI agent architectures, autonomous development sandboxes (like Antigravity and Cursor), and rich datasets, we build, deploy, and operate a portfolio of programmatic micro-SaaS tools, high-yield arbitrage applications, and data-driven platforms rapidly and efficiently. Right now, our core team is lean (just the founders). We are scaling aggressively and need an AI Operations Manager to act as our technical producer, air traffic controller, and human-in-the-loop gatekeeper to keep our production conveyor belt running flawlessly. We don’t need a traditional Senior Software Engineer who wants to write hundreds of lines of boilerplate code by hand. We need a systems-oriented, tech-forward product operator. You will sit inside our AI management dashboards, directing and moderating parallel AI agent loops as they build features, handle data pipelines, and deploy code. You will be the bridge between our strategic product vision and our autonomous AI engineering engine, ensuring quality, preventing agent sprawl, and maintaining our active digital properties. Core Responsibilities AI Agent Pipeline Oversight (Air Traffic Control): Monitor parallel, multi-step autonomous agent loops across multiple workspaces. Ensure coding agents stay on track, resolve system execution blockers, and don't burn API tokens on infinite validation loops. Human-in-the-Loop Git Management: Review the AI-generated "Artifacts," preview builds, and code changes. Safely merge approved AI code into main Git branches and push updates to production via Vercel/Netlify/Google Cloud. Operational & Site Maintenance: Keep our fleet of live websites running smoothly. Monitor basic server uptimes, keep API endpoints and subscription tokens funded, and track central error logs. Property Moderation: Oversee basic user feedback loops, flag database anomalies, and keep our dynamic database updates (like SQLite/PostgreSQL automated inputs) running without data drift. What We Are Looking For Deep AI Native Literacy: You live in the modern AI tech ecosystem. You are intimately familiar with LLMs, AI coding environments (Cursor, Antigravity, Replit, GitHub Copilot Workspace), and programmatic workflows (MCP servers). Git & Stack Literacy: You must have strong Git literacy (branching, merging, PR reviews). While you don't need to be a coding wizard, you need a solid understanding of modern web stacks (e.g., Next.js, FastAPI, Python, Supabase, Tailwind) so you can spot when an AI agent is making a sloppy structural decision. Extreme Product Intuition: You can look at an AI-generated UI preview and instantly tell if it functions properly, flows logically for a human user, or if the agent cut a corner with a placeholder. The "Hacker/Founder" Mindset: You excel in high-velocity, low-friction environments. You value moving fast, testing live apps, and iterating quickly over corporate perfectionism. Why Join Aria Technology Solutions? The Future of Software: You will work on the absolute frontier of the "Vibe-Coding" economy, learning how to leverage AI to scale digital equity at a rate traditional software teams cannot match. Zero Bureaucracy: You report directly to the founders. If something works, we launch it immediately. Portfolio Variety: You won't be bored working on one legacy corporate enterprise tool for a year. You will help launch, operate, and maintain dozens of different innovative apps, keeping your days dynamic and high-impact. How to Apply To prove you are an operator who reads the details and doesn't just copy-paste an automated AI proposal, please start your cover letter with the phrase: "Ready for the conveyor belt." Briefly tell us about a time you used AI toolsets (like Cursor, custom scripts, or agents) to build or launch something quickly, and your comfort level with managing Git branches.

Overview We’re looking for an experienced AI engineer or AI systems builder to help us design and build an internal intelligence layer that turns fragmented customer data into actionable growth opportunities. Right now, customer insights live across multiple disconnected systems — CRM notes, product usage data, emails, support tickets, and spreadsheets. While the data exists, it is not structured in a way that helps us proactively identify expansion opportunities, churn risks, or account-level next steps. We want to build an AI-driven system that continuously synthesizes this information and helps our team understand: * What is happening inside each account * Where expansion or upsell opportunities exist * Which accounts are at risk and why * What the next best action should be for each customer ⸻ What You’ll Build You will design and implement an AI system that can: * Ingest structured and unstructured data (CRM, emails, notes, product signals) * Build dynamic “account intelligence profiles” for each customer * Identify patterns across accounts (usage drops, feature gaps, expansion signals) * Generate clear, human-readable account summaries * Recommend next-best-actions for sales, customer success, or leadership * Surface expansion opportunities based on behavioral and contextual signals * Flag risk signals early with supporting reasoning ⸻ Ideal Output For each account, the system should be able to generate: * A concise account narrative (“what’s going on here”) * Key signals and anomalies * Expansion opportunities (with rationale) * Risk factors (churn or stagnation indicators) * Suggested actions for the team this week * Confidence level and supporting evidence ⸻ Why This Matters We are sitting on a large amount of customer data, but most of it is passive. The goal is to turn it into an active intelligence system that helps our team: * Prioritize the right accounts * Increase expansion revenue * Reduce churn risk * Spend time on the highest-impact opportunities This becomes a core internal system that directly impacts revenue efficiency and customer outcomes. ⸻ Ideal Candidate We’re looking for someone with experience in: * LLM-based systems and agentic workflows * Data pipelines and multi-source data ingestion * Prompt engineering + structured reasoning systems * CRM systems (Salesforce, HubSpot, etc.) * Customer analytics / product analytics * Building internal AI tools or copilots * Backend + API integration work Bonus if you’ve worked on: * RevOps tooling * Customer success platforms * Data enrichment or account intelligence systems * SaaS growth analytics ⸻ Deliverables * System architecture for AI customer intelligence layer * Data ingestion and normalization approach * Prompting / reasoning framework for account analysis * Prototype system (or working MVP) * Output format for account intelligence reports * Documentation for internal expansion and scaling * Recommendations for tooling (build vs buy decisions) ⸻ Engagement This starts as a project-based build, but could expand into a long-term role as we scale the system across our entire customer base and additional workflows. ⸻ To Apply Please include: * Examples of AI systems or agentic workflows you’ve built * Experience integrating LLMs with real business data * Your recommended architecture for a system like this * Any clarifying questions you’d want answered before starting

ElevenLabs Conversational AI Expert — Long, Multi-Node Voice Agents with Tool Calls Project type: Hourly Experience level: Expert Duration: Short-term engagement with potential for ongoing work About the project We're building voice agents on ElevenLabs Conversational AI (Agents Platform) that run long, complex calls of 20+ nodes in the workflow builder, with multiple tool/function calls along the way. The agent is embedded directly into our app (using the ElevenLabs SDK) rather than the ElevenLabs widget. The agents work, but we're fighting duplicate questions/answers. The agent re-asks questions it already asked, or repeats information it already gave, at different points in the call. We need someone who has actually built and shipped long-running ElevenLabs voice agents (not just simple single-prompt bots) to help us fix the structural setup so calls stay coherent end to end. That covers workflow/node architecture, state handling, prompt design, tool orchestration, and our client-side integration. What you'll do ● Audit our current agent: workflow node structure, system/node prompts, tool definitions, and conversation flow. ● Audit our client-side integration (the ElevenLabs SDK embedded in our app): session/connection handling, event handling, client tools, and how local app state stays in sync with the conversation. Reconnects, double-fired events, or repeated client-tool calls can also cause re-asks. ● Diagnose the root causes of the duplicate question/answer behavior. Possible culprits include context/state not being tracked across nodes, overlapping node responsibilities, prompt ambiguity, retrieval/knowledge-base issues, or client-side state/event problems. ● Redesign the node graph and transitions so each node has a clear, non-overlapping job and the conversation can't loop or re-ask. ● Improve state/variable management across nodes: dynamic variables, captured data, and how it's passed forward so the agent "remembers" within a call. ● Tighten tool/function calling: when tools fire, how results are handled, error/timeout handling, and avoiding redundant calls. ● Address context-window and long-call degradation, plus turn-taking behavior that causes drift. ● Recommend the right structural patterns for flows this long (single agent vs. multi-agent/agent transfer, sub-agents, branching). ● Document the fixes and the patterns so our team can maintain and extend the setup. You're a strong fit if you have ● Demonstrable hands-on experience with ElevenLabs Conversational AI / Agents Platform. Please reference specific agents or projects you've built. ● Experience with the workflow/node builder for branching, multi-step calls, not just a single system prompt. ● Experience embedding ElevenLabs in a custom app via the SDK (React/JS, WebRTC/WebSocket), not just the drop-in widget. ● Solid grasp of tool/function calling (client tools and server tools/webhooks), including error handling. ● Strong prompt engineering for voice, plus understanding of LLM context windows, state, and conversation memory. ● Experience debugging long conversations for looping and repetition, including intermittent, hard-to-reproduce cases. ● Bonus: knowledge base / RAG, dynamic variables, multi-agent transfer, post-call analysis, and the ElevenLabs API/SDK. To apply, please include 1. A short description of a long, multi-node ElevenLabs agent you built: how many nodes, what tools, and what it did. 2. How you'd approach diagnosing duplicate question/answer issues in a 20+ node flow (a quick paragraph, since we want to see how you think). 3. Your availability and rate. Applications that just say "I'm an AI expert" without specific ElevenLabs experience will be skipped. We're looking for someone who has lived in this platform.

AI SYSTEMS ENGINEER Agentic AI, Multi-Agent Systems & Secure AI Workflows (U.S.) Remote • United States We're building production AI systems designed for enterprise environments. We're looking for exceptional AI systems engineers who enjoy solving difficult systems problems – not just writing code. Our work sits at the intersection of agentic AI, software architecture, enterprise systems, governance, security, and operational intelligence. We design AI systems that improve how organizations operate while meeting the standards required for production deployment. We value engineers who think in systems, challenge assumptions, and care deeply about building technology that is reliable, understandable, secure, and useful. If you're motivated by difficult engineering problems, thoughtful architecture, and building production AI systems for enterprise organizations, we'd like to hear from you. WHAT YOU'LL HELP BUILD Examples of the types of systems we design include: - Multi-agent AI systems - Enterprise AI assistants - Secure AI workflows - Enterprise workflow automation - AI-powered knowledge systems - Human-in-the-loop decision support - Document intelligence - Retrieval-Augmented Generation (RAG) - AI memory and retrieval systems - AI evaluation and testing frameworks - Secure enterprise AI platforms - AI governance capabilities - Operational intelligence platforms TECHNICAL EXPERIENCE WE VALUE We're interested in engineers with experience in some combination of: - Python - AI Agent Development - LangGraph - LangChain - Large Language Models - API Development - Vector Databases - Software Architecture - Enterprise Systems Integration - Information Security Experience with OpenAI, Anthropic, Model Context Protocol (MCP), cloud infrastructure, workflow orchestration, observability, distributed systems, or regulated technology environments is also valuable. We do not expect expertise in every technology. We care far more about engineering judgment, systems thinking, demonstrated execution, and continuous learning than checking every technology box. THE PROBLEMS WE ENJOY SOLVING The engineers who thrive here enjoy questions like: - How should multiple AI agents coordinate work? - How should humans remain in control of important decisions? - How should production AI systems scale safely? - How should memory be designed for enterprise AI? - How should AI systems balance operational performance with governance, security, and reliability? - How should AI systems create measurable business value? If those questions excite you, you'll probably enjoy working with us. WHAT MAKES SOMEONE SUCCESSFUL HERE We're looking for engineers who: - Think in systems rather than individual features. - Care deeply about production quality. - Enjoy solving ambiguous technical problems. - Communicate complex ideas clearly. - Balance speed with sound engineering judgment. - Build practical solutions rather than chasing hype. - Continuously learn, experiment, and improve. We're significantly more interested in systems you've built than technologies you've used. Please provide specific examples that demonstrate your role, engineering decisions, and measurable outcomes. We recognize that many engineers use AI as part of their workflow. You're welcome to do the same. However, your application should accurately reflect your own experience, judgment, and technical thinking. We respect the confidentiality of your current and former employers, clients, and partners. Please do not include proprietary or confidential information in your application. Describe your work at a level that demonstrates your engineering approach without disclosing protected information. PROFESSIONAL STANDARDS We value integrity, sound engineering judgment, and respect for intellectual property. Please do not include confidential, proprietary, export-controlled, or other non-public information belonging to your current or former employers, clients, or partners in your application or work samples. We're interested in your engineering approach, architectural thinking, and problem-solving methodology – not protected information belonging to others. If you share code, architecture diagrams, technical documentation, or project examples, please ensure you have the legal right to do so and identify any material open-source or third-party technologies where appropriate. By submitting application materials, you represent that you have the legal right to share them and that doing so does not violate any confidentiality, intellectual property, employment, consulting, or other contractual obligations. Any engagement, if offered, will be subject to a separate written agreement covering confidentiality, intellectual property ownership, compensation, and other applicable terms. Submission of an application or participation in the evaluation process does not create any employment, independent contractor, partnership, joint venture, agency, fiduciary, or other business relationship with 26ers AI, nor does it obligate either party to enter into any future engagement. 26ers AI reserves the right to evaluate applications, discontinue discussions, modify the hiring process, or decline to pursue any engagement at its discretion. Nothing in this posting should be construed as an offer of employment or an offer to contract.

I'm looking for a skilled developer who can move fast, think creatively, and act more like a partner than a contractor. If you're someone who builds things quickly, brings ideas to the table without being asked, and genuinely cares about creating great experiences for end users, keep reading. -—————- **What You'll Be Working On:** This product sits at the intersection of AI, data, and customer experience. At its core, it needs to: - Monitor and process large volumes of data** in or near real time — surfacing insights, anomalies, and patterns that matter. - Send automated personalized outreach via SMS and email — based on the data signals and triggers, the system should be able to generate and send personalized messages to the right person at the right time, without manual intervention - Integrate with POS systems and CRMs** — pulling, syncing, and acting on data across platforms - Deliver a seamless, intuitive customer-facing experience** — this isn't just a backend tool, how users feel when they interact with it matters enormously - Be built on top of **Claude (Anthropic's AI)** using **Claude Code** as a core part of the development workflow We're in early stages, which means we're figuring things out as we go. That's not a warning — it's an opportunity for the right person. --- **What I'm Looking For:** - Hands-on Claude Code experience** — you've actually built with it, not just read about it. Experts only please - CRM and POS integration experience** — you've connected to platforms like Salesforce, HubSpot, Square, Toast, Lightspeed, or similar, and you know the quirks - Data monitoring and pipeline experience** — you've built systems that ingest, process, and surface meaningful signals from large datasets - Customer experience mindset** — you think about the end user constantly, and you've built tools that real customers interact with - Fast builder, fast thinker** — you're comfortable with ambiguity, can ship quickly, and know how to iterate without everything being perfectly defined upfront - Collaborative and opinionated** — I want someone who pushes back, brings ideas, and helps shape where this goes — not someone waiting for a spec I also want to **learn as we build** — so being able to explain what you're doing and why, in plain terms, is important to me. --- A Note Before You Apply: Please only submit a proposal if you have deep, hands-on experience with Claude Code — not surface-level familiarity, not currently learning it. We're looking for someone who has already put in the reps, knows the ins and outs, and can hit the ground running from day one. We respect your time and ask that you respect ours. If Claude Code isn't already a tool you've mastered, this isn't the right fit. **When You Apply, Please Include:** - Specific examples of tools you've built that involve **CRM or POS integrations** — name the platforms and describe what you built - Examples of **data monitoring or real-time data tools** you've worked on — what did it track, how did it work, what was the scale? - Any **AI-powered products** you've shipped, especially using Claude or other LLM APIs — links, screenshots, or descriptions - How you approach building something when the full picture isn't defined yet - A thought or two on what makes a truly great AI-powered customer experience — I want to see how you think --- **What This Could Become:** This is the beginning of something bigger. The right person won't just be a hire — they'll grow with the product. There's real potential for a long-term working relationship as this evolves.

Senior Software Engineer (AI-Focused, Contract – US) Position Summary W Energy is seeking a Senior Software Engineer (Contract) to help drive the integration of AI capabilities into our core platform. This role is focused on building AI-powered product features, not just experimenting with models—embedding intelligence directly into workflows across our upstream and midstream solutions. You’ll design and implement AI-driven functionality that improves automation and user experience. This includes leveraging LLMs, machine learning models, and modern AI tooling within a production SaaS environment. This is a hands-on role for someone who can move quickly, make pragmatic decisions, and bring AI concepts into real, scalable product features. Responsibilities • Design and implement AI-powered features within the platform (e.g., automation, recommendations, copilots) • Integrate LLMs and/or ML models into existing services and workflows • Evaluate, select, and optimize AI tools, APIs, and frameworks for production use • Collaborate with Product to translate business problems into AI-driven solutions • Build and maintain scalable backend services to support AI functionality • Profile, test, and optimize performance of AI-integrated systems • Ensure reliability, security, and cost-efficiency of AI components in production • Contribute to architecture decisions around AI integration and system design • Partner with engineering teams to embed AI into existing applications without degrading stability Requirements • 5+ years of experience as a software engineer in a SaaS or cloud-based environment • Strong backend engineering experience (RoR and/or Golang preferred) • Experience integrating APIs and working within distributed systems • Hands-on experience with AI/ML tools (e.g., OpenAI, Anthropic, Hugging Face, or similar) • Experience building or integrating AI-powered features into applications (not just experimentation) • Strong understanding of data flow, system design, and performance optimization • Experience with relational databases (SQL Server or similar) • Familiarity with microservices architecture, Kubernetes, and CI/CD pipelines • Experience deploying applications in Azure or similar cloud environments • Strong problem-solving skills with ability to work in ambiguous, fast-moving environments • Builder mindset—someone who can take an idea and turn it into a working feature quickly • Pragmatic approach to AI (focus on value, not hype) • Ability to work independently in a contract environment while collaborating closely with internal teams • Strong communication skills and ability to explain AI concepts to non-technical stakeholders Preferred • Experience with prompt engineering, embeddings, or retrieval-augmented generation (RAG) • Exposure to model evaluation, fine-tuning, or AI performance monitoring • Experience with event-driven architectures or real-time data processing • Background in energy, fintech, or other complex data-driven industries