- Fixed price
- Expert
- Est. budget: $2,000.00
We are hiring an AI Engineer with strong hands-on experience building and shipping real AI products. Requirement: If you don't have a GitHub profile to share, this role is not a fit. What we’re looking for: • Strong experience in AI/ML engineering • Ability to build, test, and deploy production-ready AI systems • Practical experience working on real-world AI projects To apply: Please share your portfolio, past AI projects, and relevant work samples. Applicants without portfolio will be ignored.
- Hourly: $70.00 - $85.00
- Expert
- Est. time: 1 to 3 months, Less than 30 hrs/week
Overview We're building an open-source CLI gateway for multi-agent AI orchestration — model-agnostic, MCP-native, and designed to bring any agent framework online with a single command. The repo is active, well-documented, and growing. We need an engineer to accelerate integration coverage and help attract open-source contributors. The Work Build agent templates and runnable examples for LangGraph, CrewAI, and similar frameworks Add LLM provider support (Groq, Mistral, Gemini, etc.) to the Hermes runtime Write clean, contributor-friendly code that models good PR hygiene Submit work via fork → PR → merge workflow on GitHub You Are Strong Python developer with CLI tooling experience Familiar with at least one of: LangGraph, CrewAI, LiteLLM, LangChain Comfortable with open source GitHub workflows (fork, PR, issues, reviews) Self-directed — you read docs, ask good questions, and don't wait to be unblocked Nice to Have Experience with MCP (Model Context Protocol) Familiarity with SSE, OAuth 2.1, or agent credential management Prior open source contributions Engagement Part-time to start, 20 hrs/week Fixed milestones per integration delivered Potential to grow with the project To Apply Share your GitHub profile and one example of open source work or a project that shows your Python and agent framework experience. https://github.com/ax-platform/ax-gateway
- Hourly
- Intermediate
- Est. time: Less than 1 month, Less than 30 hrs/week
Project Overview We are looking for an experienced AI workflow, process design, and prompt engineering expert to help us automate part of our sales and proposal development process. Currently, our project management team spends 4–12 hours developing a custom research plan and proposal for each active FSI lead. In busy weeks, we may work on 5–6 leads, which creates a significant time burden and slows down response time. We want to build a custom ChatGPT skill or AI workflow that can take sales notes, email context, and call notes, then help generate a research plan and proposal in our existing format. What We Need We need someone who can: Learn and map our current sales/proposal process Translate that process into a structured AI workflow Write effective prompts and decision trees Train or configure a custom ChatGPT skill/workflow Help the AI ask the right follow-up questions Generate proposal sections based on uploaded notes Recommend research scope, segmentation, targets, and options Output the final proposal in our existing template Desired Workflow The ideal AI workflow would allow us to upload notes from emails and sales calls. The AI would then ask a series of structured questions to determine how to write each section of the proposal. The AI should be able to: Recommend the appropriate research process Suggest project scope Identify demand segmentation opportunities Create tables for the proposal Recommend constituencies and companies to target Suggest research options Draft the proposal using our template Provide a strong first draft that our team can review and adjust Business Goal The goal is to significantly reduce the time spent developing research plans and proposals, especially for early-stage leads and marketing-generated opportunities. This is particularly important for new leads from companies we have not worked with before, where the probability of closing may be relatively low. We want to respond quickly and professionally without taking excessive time away from active client projects. Ideal Freelancer You should have experience with some or all of the following: AI workflow design Prompt engineering Custom GPTs or ChatGPT skills Sales/proposal automation Business process documentation B2B research or consulting workflows Template-based document generation AI-assisted decision trees Knowledge management or internal AI tools Experience with market research, consulting, or proposal development is a plus. Deliverables We expect the freelancer to deliver: A documented AI workflow/process map A set of structured prompts and instructions A functioning custom GPT, ChatGPT skill, or equivalent AI workflow Question logic for gathering missing proposal inputs Proposal section drafting logic Testing and refinement using sample lead notes Documentation so our team can maintain and improve the workflow Project Type This will likely begin as a one-time project, with potential for ongoing support as we refine the workflow and expand it to other proposal types. To Apply Please include: Examples of AI workflows, custom GPTs, or prompt systems you have built Your experience with proposal automation or business process automation Your recommended approach for this project Any questions you would need answered before starting
- Hourly: $50.00 - $100.00
- Expert
- Est. time: More than 6 months, Less than 30 hrs/week
I’m looking for a senior AI app developer who can help me build an AI-powered MVP while also guiding me through the technical decisions. This is not just a coding task. I want someone who can think through the product, recommend the right architecture, explain tradeoffs, and build the first working version. The ideal person should be comfortable with OpenAI/LLM integrations, full-stack development, database design, authentication, deployment, and startup-style MVP execution. I’d like to work with someone who can act almost like a technical partner: build the product, teach me what is being done, and help me understand how to maintain or scale it later.
- Hourly
- Intermediate
- Est. time: 1 to 3 months, Less than 30 hrs/week
Are you an experienced web developer who loves building applications, enjoys mentoring, and is excited about leveraging AI to code faster? I am looking for a sharp, collaborative technical partner to work with me live over Zoom to build out various web applications. A core part of our workflow will involve utilizing Claude (and other AI tools) to brainstorm, scaffold, and accelerate our development process. Instead of working in isolation, you will be partnering with me in real-time to solve problems, review code, architect solutions, and push projects across the finish line. What You’ll Do Live Pair Programming: Join scheduled Zoom calls to actively write, debug, and review code together. AI Collaboration: Work alongside me to prompt, refine, and implement code generated by Claude to speed up the development lifecycle. Web Application Development: Help build, test, and deploy functional, clean web applications from scratch or improve existing codebases. Architectural Guidance: Offer advice on best practices, database design, and framework selection based on project needs. What I’m Looking For Strong Technical Foundations: Proficiency in modern web development frameworks and languages (e.g., JavaScript/TypeScript, React, Node.js, Python, or similar modern stacks). AI-Fluent: You don't just know how to code; you know how to use AI tools like Claude efficiently to debug, generate ideas, and optimize workflows. Excellent Communication & Patience: Since we will be working live on Zoom, you must be a clear communicator who enjoys explaining technical concepts and brainstorming out loud. Problem Solver: A knack for breaking down complex feature requests into manageable, step-by-step development tasks.
- Hourly: $80.00 - $110.00
- Expert
- Est. time: 3 to 6 months, 30+ hrs/week
We are a small AI consulting practice that helps financial services firms put AI to work inside their business. Our clients are owner-led firms like accountants, business appraisers, financial advisors, and insurance agents. We do not sell one-off scripts or disposable projects. We build practical AI systems that take real work off these firms' plates, delivered through ongoing monthly work. Demand is growing and the bottleneck is delivery. We are looking for one delivery partner to own that side of the work with us. How it works: we handle marketing, sales, and the paid advisory session that starts each client. Once a client moves to ongoing work, you take the lead on delivery. You build the systems against the priorities we set each month, and you run the weekly client meeting as their main point of contact. We stay in for support, to translate the client's business context, and to own the relationship at the top, but week to week the client works with you. What you would own: -Building AI and agentic systems for clients -Running the weekly client meeting and being the client's day-to-day contact -Taking each engagement from kickoff through delivery on the month's agreed hours, to a standard we can stand behind Compensation is $100/hour for your hours, which include both build time and client meetings. Straightforward and paid against tracked hours. As our client book grows, so do the hours available. Who we are looking for: -Genuinely fluent building real systems with modern AI tools. -Not just familiar with them. You should be comfortable architecting and shipping working systems for non-technical business owners. -Client-ready. You can run a working session, explain technical things plainly to a non-technical owner, and hold a client relationship week to week. -Native or fluent English. You are in front of clients every week, so clear, natural communication is non-negotiable. -Strong general technical judgment. The specific stack matters less than the ability to find the right solution and build it. -Reliable. We scope the work and stand behind it, so we need to count on what you deliver and how you handle the client. Who this is not for: anyone looking to own sales or pricing, anyone who only wants to build quietly and never talk to a client, and anyone new to this work hoping to learn on the job. To apply, tell us briefly: the most relevant AI system you have built and what it did for the business, how comfortable you are leading client calls, and how you approach building these systems. Start your reply with the word "Agentic" so we know you read this in full. Applications without it will not be reviewed. We will move quickly with the right person.
- Hourly: $65.00 - $500.00
- Expert
- Est. time: 1 to 3 months, Less than 30 hrs/week
Senior AI/ML Engineer / Claude architect — Legal Tech FirmProfit AI is the operational backbone of the modern law firm. We automate law firm operations end to end, and we're looking for a top-tier AI/ML engineer to help us build the next major platform in legal tech. We need a true expert. Someone deeply proficient with Claude and modern LLM architecture who has shipped real products at a high level. You're fluent across the full stack with Node.js, React, Postgres, MongoDB etc... and you have hands-on experience building with LangChain, LangGraph, MCP, and AWS Bedrock. We're not looking for someone who's read about LLMs. We're looking for someone who has shipped agents, orchestration layers, and production AI systems that real users depend on every day. Our current team is 8 engineers, we have firms signed and live, and we're moving fast. This is a chance to come in early, and have your work in the hands of customers within weeks. Contract to start, with a long-term path for the right person. Reply with the most impressive AI product you've shipped.
- Fixed price
- Intermediate
- Est. budget: $8,000.00
Engagement Overview I am the CEO and principal attorney of a small law practice specializing in campaign finance, lobbying regulation, FARA, nonprofit law, and government ethics. My five-person team — a junior partner, two associates, and an executive assistant — recently integrated into a larger firm. I am looking for an experienced Claude/AI automation builder for a phased engagement to design, build, and deploy a suite of interconnected agents and automations. This brief covers three phases. Phase I (Inbox Triage) is the highest immediate priority and the natural starting point. Phases II and III follow sequentially. Strong candidates will be evaluated on Phase I but should demonstrate familiarity with the full roadmap. This is a paid engagement. Scope, timeline, and rate are open to discussion. Technology Stack Email: Gmail (personal Pro account — not firm infrastructure) AI: Claude (Anthropic) via MCP or API Task and project management: Notion (existing workspace; routing tables, matter tracking, and timesheet structure already in place) Calendar: Google Calendar Internal chat: Google Chat Document storage: Google Drive (primary); local hard drives on iMac and MacBook Pro (secondary) Matter management / DMS: iManage (larger firm system — integration via dedicated ingestion email address) Voice notes: Plaud (AI note-taker) Signing platform: TBD — candidates should ask during scoping Out of scope: Signal and iMessage — encrypted platforms with no API access; manual forwarding convention only Confidentiality Requirements This is a law practice. Attorney-client privilege and work product protection apply to all client communications and matter-related documents. These are not compliance checkboxes — they are professional obligations with real consequences. The successful candidate must: • Execute a non-disclosure agreement prior to engagement • Demonstrate genuine understanding of why data handling matters in a legal context — not just technically, but professionally • Never use client names, email content, routing data, or document content for training, testing, or demonstration purposes • Work exclusively within the client's authenticated accounts — no third-party data stores outside the approved stack • Design systems that minimize data exposure — process and route, do not store unnecessarily Generic proposals that do not address confidentiality specifically will not be considered.   Phase I — Inbox Triage Agent Real-time classification and routing of inbound Gmail, with a daily digest to the executive assistant. Objective The principal attorney's Gmail inbox receives high volumes of email across clients, matters, and categories of widely varying priority. The goal is an agent that processes every inbound message, classifies it, routes it to the correct person automatically, and ensures nothing drops — without overloading the executive assistant with triage work she should not be doing. Two-Stage Routing Logic Stage 1 — Sender Classification Every inbound email is classified against a tiered contact list maintained in a Notion database: MVC: Most Valuable Clients — 5 to 10 contacts. Highest priority. HVP: High Value People — 10 to 20 contacts. Some overlap with MVCs. Principal attorney, unless task-type rule applies All other clients: Roster managed in Notion with assigned attorney(s). Assigned attorney(s) per Notion client record Catch-All: Anyone not in the contact table — prospects, opposing counsel, vendors, bar association, etc. Generate executive assistant daily digest Stage 2 — Task-Type Classification (MVCs only) For MVC contacts, a second classification layer routes based on the nature of the request. Rules are client-specific. Examples: • Scheduling requests → Executive assistant • Contracts and approvals → Designated associate(s) per client record • Strategic and substantive legal matters → Principal attorney Task-type rules are defined per MVC client and must be configurable without developer involvement. Routing Table — Notion All contact and routing data lives in an existing Notion database. The agent reads from it at runtime. Required fields: • Contact name and/or email domain • Tier (MVC / HVP / Standard / Catch-All) • Assigned attorney(s) for Standard clients • Task-type override rules for MVCs The executive assistant must be able to add, edit, and re-tier contacts without touching code. This is a hard requirement. Routing Output Candidates should propose their recommended approach from among the following, based on current Gmail MCP capabilities: • Apply Gmail label and/or forward to assigned attorney's address • Create a pre-addressed draft for principal attorney review before sending • Log routing decision to Notion with email link and recommended assignee Please address this question directly in your proposal — it is a key evaluation criterion. Daily Executive Assistant Digest Once per day at a configurable time, the agent generates a digest delivered to a designated Notion page covering all catch-all emails from the prior 24 hours. Each entry includes: sender, subject, timestamp, and a one-line AI summary of the email's apparent purpose.   Phase II — 5 AM Daily Brief A structured morning brief delivered to Notion each day before 5 AM, aggregating schedule, tasks, workflow status, news, and forward-looking context. Objective The principal attorney starts each day across multiple locations and needs a single, consolidated view of what matters — professional and personal — without opening email. The brief is delivered to a dedicated Notion page and covers the sections below in the following order. Section 1 — Daily Schedule Full calendar for the day pulled from Google Calendar. All events, calls, and commitments in chronological order. Section 2 — Open Projects and Undone Tasks Two sub-sections: (a) MVC high-value work — open projects and incomplete tasks for Most Valuable Clients, filtered to substantive legal work only; and (b) Personal — all open personal projects and tasks without exception. Personal items are comprehensive by design: if it is not surfaced here, it will be forgotten. Source: Notion task and project database. Section 3 — Blocking What is the principal attorney specifically holding up? Items where others in the firm are waiting for a review, decision, approval, or action. Source: Notion matter and task records where assignee or status indicates the ball is in the principal attorney's court. Note to builder: this section requires careful logic design. The agent must infer from status fields and assignee data what is genuinely waiting on the principal attorney versus what is simply unresolved. Work with client during onboarding to define the exact field logic. Section 4 — News Digest Industry News Curated digest of overnight developments in: campaign finance law and FEC activity, election administration, lobbying regulation (federal and state), nonprofit political activity, and government ethics. Format: short summary of each item with a link to the full article. Aim for signal, not volume — 5 to 10 items maximum. US Political News 5 to 10 headlines with links covering: presidential politics, US Senate and House elections, and major gubernatorial races. Stories people are actually talking about, not wire service filler. Section 5 — Firm Workflow Matter-level status summary pulled from Notion, organized by client tier and activity: Status Definition Closed Completed yesterday Moving Action taken yesterday Paused No action yesterday Stuck No action in five or more days Client groupings: MVCs (non-high-value work), Standard clients (all work), and any other open matters. Section 6 — One Month Look Ahead Rolling 30-day forward view pulled from Google Calendar covering: regulatory filing dates and compliance deadlines, matter-level deadlines, client birthdays, holidays, and planned vacations or travel. Anything that requires preparation or awareness in the next 30 days. Section 7 — Personal Financial Summary (If Feasible) Summary of personal financial position pulled from Monarch Money, if an API or MCP connector is available. Candidates should investigate Monarch's API access and address feasibility in their proposal. If not currently feasible, this section is omitted without affecting the rest of the brief. Delivery Notion only — not email. A dedicated page refreshed each morning before 5 AM. Previous day's brief should be archived, not overwritten.   Phase III — Night Maintenance Three nightly agents that run after close of business: timesheet creation, document filing preparation, and Plaud note routing. All outputs are delivered to Notion for principal attorney review. Part 1 — Timesheet Creation Objective Each evening, the agent reviews the day's activity across three sources and populates a timesheet in an existing Notion template for the principal attorney's review and finalization. Sources • Google Calendar — all events and calls attended • Gmail sent items — emails sent that day, grouped by client/matter where inferable • Google Chat — internal messages sent, grouped by thread/matter where inferable Note to builder: Google Chat API access will need to be confirmed alongside Gmail and Calendar MCPs. Confirm availability and any OAuth scope requirements in your proposal. Output: Populated Notion timesheet using existing template structure. Principal attorney reviews each morning, adjusts entries as needed, and finalizes. The agent does not finalize — it drafts. Part 2 — Document Filing Objective Each evening, the agent surfaces documents created or edited that day for the principal attorney's review. The attorney flags finals, and the agent forwards them to the firm's iManage ingestion email address for filing. Sources • Google Drive — documents created or modified that day • Local hard drives — iMac and MacBook Pro Note to builder: local hard drive access requires a locally-running component (daemon, Claude Code instance, or folder-watching script) on each machine. Please address your proposed approach to this in your proposal. Alternative approach for consideration: a designated 'Ready to File' folder on each machine that syncs to Google Drive. The attorney drags filing-ready documents into this folder throughout the day; the agent watches the folder and processes from there. Simpler architecture, device-agnostic, and builds a consistent filing habit. Candidates should evaluate and recommend. Output: A Notion page listing all documents surfaced for that day, with document name, location, and last-modified time. Principal attorney marks finals. Agent forwards marked documents to the iManage ingestion email address. iManage filing is handled by firm IT from that point — no direct iManage API integration required. Part 3 — Plaud Note Routing and Archiving Objective: The principal attorney uses a Plaud AI note-taker on calls and meetings. Each evening, the agent pulls new Plaud summaries, routes them to the appropriate team members, archives a copy to Notion tagged to the relevant client matter, and deletes the underlying audio and transcript from Plaud's platform and the local device. Prerequisite — Plaud API Plaud API or webhook access is a prerequisite for this part. Candidates must investigate and confirm availability before scoping. If Plaud does not currently support programmatic access, this part will require a manual export step as a workaround — please address both scenarios in your proposal. Routing Logic: Similar in structure to Phase I inbox triage routing (MVC/HVP/Standard tiers with task-type overrides) but with distinct rules to be defined with the client during onboarding. Do not assume inbox triage rules apply directly. Archiving: One copy of each Plaud summary is saved to Notion as a note, tagged to the relevant client matter. Tagging logic to be defined during onboarding. Deletion: After successful routing and archiving, the agent deletes: (a) the audio and transcript from Plaud's platform via API, and (b) any local copies on the principal attorney's devices. Local deletion requires the same locally-running component described in Part 2. Candidates may propose a unified local agent that handles both Part 2 and Part 3 local operations.   What I'm Looking For Strong candidates will have: • Demonstrated experience building Claude-based automations or agents — not general AI experience • Hands-on experience with Gmail MCP, Google Calendar MCP, and Notion MCP (or equivalent API integrations) • Ability to build systems that non-technical users can maintain — editability and simplicity are as important as technical sophistication • Comfort with phased delivery — Phase I first, Phases II and III following sequentially based on performance • Experience with professional services clients (legal, financial, consulting) is a meaningful plus • Willingness to execute an NDA and work within a legally sensitive environment What to Include in Your Proposal Please address the following specifically. Proposals that do not engage with these questions will not be considered. • Your proposed technical architecture for Phase I — how you would connect Gmail, Claude, and Notion • Your answer to the Gmail MCP routing output question in Phase I (labeling vs. drafts vs. Notion logging) — what is actually supported and what do you recommend • Your assessment of Plaud API availability and your proposed approach for Phase III Part 3 • Your assessment of Monarch Money API feasibility for the Phase II financial summary section • Your proposed approach to local hard drive access for Phase III Parts 2 and 3 — daemon, sync folder, or other • A comparable project you have delivered — describe the client type, the stack, and what made it work • Your estimated timeline and rate for Phase I, and a rough order-of-magnitude estimate for Phases II and III • Confirmation that you are willing to execute an NDA prior to engagement I am looking for someone who has read this brief carefully and has a specific, informed point of view on how to build it. This is phase one of a longer automation roadmap and the right candidate will be a long-term partner, not a one-time contractor.
- Hourly: $20.00 - $40.00
- Intermediate
- Est. time: 1 to 3 months, Less than 30 hrs/week
I need someone to help me set up AI automations for several different platforms and tie them all together. I want to add a way to post automatically to various platforms. The ideal candidate will have experience in AI automation and integration, and be able to work with multiple platforms seamlessly.
- Hourly: $70.00 - $85.00
- Expert
- Est. time: More than 6 months, 30+ hrs/week
I need an expert senior software engineer that can provide consulting services around implementation best practices of LLM's and AI into existing application workflows. i.e. leveraging AI to extract data from a document as part of an ingestion pipeline.