We’re hiring a Senior AI Engineer to help deliver AI healthcare product fix which is in production. Must haves Build multi-agent systems (LangGraph or equivalent) Shippped RAG over enterprise docs/knowledge bases Handled agent memory and context management Wires tools/APIs into complex workflow automation 5+ years Python; strong FastAPI in production Shipped LLM apps used by real customers Hands-on with LangGraph/LangChain, vector DBs, PostgreSQL, Redis, Docker Nice-to-have: AWS, Azure, or GCP deployments

Help ship our AI product: LLM architecture, integrations, and a production pipeline that’s fast, reliable, and accurate. You’ll work on Custom AI systems: LLM integration, RAG, agents, or LoRa fine-tuning Prompt pipelines, tool/MCP calling, structured outputs Vector search (Pinecone, Weaviate, Qdrant, Chroma, pgvector) Latency, cost, and context efficiency across OpenAI, Anthropic, and OSS models Backend wiring via REST/webhooks Evals: hallucination checks, retrieval quality, output validation Requirements Strong Python; TypeScript/Node a plus LangGraph, LlamaIndex, AutoGen, CrewAI, or direct SDKs (OpenAI, Anthropic, Hugging Face) Vector + relational/NoSQL data stores Docker, AWS/GCP/Azure, FastAPI/Flask, serverless Solid grasp of embeddings, RAG, fine-tuning, function calling, and agent workflows

Looking for an experienced AI developer to help build an AI agent using Claude. Requirements: Experience building AI agents and autonomous workflows Strong experience with Claude and Anthropic models Ability to integrate external data sources and APIs Experience deploying production-ready AI solutions Please include: Examples of similar AI agent projects you've built Your experience with Claude Your recommended tech stack Estimated timeline and cost Looking to start immediately.

We’re seeking a seasoned AI Architect / Senior LLM Engineer to assess an enterprise healthcare AI platform. If it’s a strong match, you’ll drive the architecture and delivery of AI systems that streamline clinical operations, automate admin workflows, and give care teams reliable access to medical knowledge via modern LLM capabilities. You should have shipped production Agentic AI, multi-agent systems, RAG pipelines, and LLMOps on current AI frameworks and cloud infrastructure. This starts as a short engagement focused on architecture review and targeted issue remediation.

About us We're a growing multi-location dental group in South Florida. We've already designed a fleet of 8 internal automation agents — complete written specs, working code templates, and infrastructure in place. We need a skilled developer to build and deploy them. This is implementation work with clear specs, not open-ended R&D. What you'll build Python automation agents that pull data from our practice management system's REST API (auth pattern already proven in production scripts you'll receive) Claude API integrations (drafting appeal letters, patient texts, weekly analyst reports) with a strict de-identification pattern we'll teach you Firebase (Firestore) reads/writes and light updates to existing web dashboards (deployed via Netlify) Scheduling via Windows Task Scheduler; simple HTML email reports Occasional work with HubSpot API and Google Sheets You're a fit if you have 3+ years Python, comfortable with REST APIs, JSON, and error handling Firebase/Firestore experience Experience integrating LLM APIs (Anthropic/OpenAI) Ability to work from an existing codebase and follow written specs precisely Strong written English and reliable weekly availability (EST business hours overlap) Healthcare/HIPAA experience a plus, not required — but you must be willing to learn and follow our PHI handling rules exactly Requirements (non-negotiable — please do not apply if you cannot meet all of these) Located in the United States with US work authorization. No offshore contractors or agencies. Completed W-9 on file before any work begins Background check required (we order and pay for it) Signed NDA and HIPAA Business Associate Agreement (BAA) required before you are granted any access to systems containing Protected Health Information (PHI). This is a healthcare environment — no exceptions. Video call interview with camera on; government ID verification All access granted via individually credentialed accounts (no shared logins), revocable by us at any time How we'll work Paid test task first: build one small agent (~4–6 hrs) from our spec using our template. Paid at your full rate. Then ~10–20 hrs/week building out the remaining agents, one at a time, each with a written "done when" acceptance test After the initial build-out (est. 60–100 hours total), ongoing part-time maintenance and new features for the right person Weekly check-in call; async otherwise To apply Briefly describe a Python + API automation project you built (what it pulled, what it produced, how it was scheduled) Confirm you're US-based and willing to complete a background check and sign a BAA Your hourly rate and weekly availability Start your proposal with the word "HUDDLE" so we know you read this

We need an AI automation developer to build a tool that reconciles clinical trial site invoices against contracted terms and EDC records. Invoices come in PDF, scanned PDF, and structured formats. The tool should extract line-item billing data, compare billed items and amounts to contracted fee schedules, cross-check activity against EDC exports, and generate a discrepancy report identifying overbilling, underbilling, unsupported billing, and missing items. We want this built around the Claude API, so hands-on experience integrating Claude or similar LLMs into document extraction and comparison workflows is essential. Deliverable is a working script/tool with documentation and a short demo using sample data. Clinical trial, CRO, or EDC experience is a plus.

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.

AI/NLP Engineer for NIH SBIR Phase I Project About the Project I am the founder of an early-stage startup developing an AI-powered platform intended to improve regulatory decision-making and document quality in clinical and human-subjects research. The project was submitted to NIH as a Phase I SBIR application. We have received an Intent to Fund notification and are currently completing NIH’s Just-in-Time requirements before a final award decision. Funding is not official until NIH issues a formal Notice of Award. Immediate Need I am seeking an experienced AI/NLP Engineer who would be interested in joining the project as Senior/Key Personnel and performing the funded development role if NIH issues the award. Because of the current NIH timeline, the selected candidate must be available this week to complete several administrative requirements: * NIH Biographical Sketch Common Form * NIH Current and Pending (Other) Support Common Form * Required Research Security Training * Basic information needed for the proposed personnel update I will provide clear instructions and support throughout the process. No technical development work will be requested before an award is issued and a paid agreement is in place. Funded Role If NIH accepts the personnel update and issues the award, the position would include: Budget: $38,350 Level of effort: 3.4 calendar months or ≈ 589 hours Project period: Approximately 6–12 months Work arrangement: Remote Most development work is expected to occur during the first several months, followed by testing, refinement, documentation, and integration support. The final milestones, schedule, payment structure, deliverables, and contract terms would be confirmed before paid work begins. Anticipated Responsibilities The AI/NLP Engineer would work with the Director of Software Engineering, Full Stack Developer, Data Architect, UX/UI Designer, and regulatory experts to: * Design and implement the Phase I AI/NLP architecture * Develop a retrieval-augmented generation system grounded in authoritative regulatory materials * Build document-ingestion, indexing, retrieval, and analysis pipelines * Analyze research protocols, informed-consent forms, and related documents * Develop structured, source-grounded outputs with traceability * Implement safeguards for hallucinations, unsupported conclusions, and prompt manipulation * Develop methods for evaluating retrieval quality, factual accuracy, robustness, and expert agreement * Integrate the AI/NLP components with the broader application * Document the architecture, evaluation methods, limitations, and results Relevant Experience Strong candidates will have experience in several of the following: * Python-based AI or NLP development * Large language models and RAG systems * Embeddings, vector databases, hybrid search, or reranking * Long-document processing and information extraction * Prompt design and structured model outputs * LLM evaluation and hallucination testing * Prompt-injection defenses and responsible AI safeguards * API development and integration * Clear technical documentation and team collaboration Experience in healthcare, clinical research, legal technology, compliance, or another accuracy-sensitive field is helpful but not required. Please briefly let me know: 1. A summary of your relevant AI/NLP, LLM, or RAG experience. 2. Whether you would be available to complete the required NIH administrative forms this week. 3. Whether you would be available to perform approximately 3.4 calendar months of effort (about 590 hours) over the Phase I project if funded. Selection and paid work are contingent on NIH accepting the personnel update and issuing a formal Notice of Award.

We are a research group at Stanford University studying human workflows. We are seeking a freelance Software Engineers (SWEs). Data Scientists, AI Specialists, and Forward Deployed Engineers (FDEs) who commonly use AI tools for coding. The project involves completing a coding task or data analysis task(s) (~1 hr each) while using an open-source recording tool to capture your computer-use activities. If you have experience with completing coding projects with Claude Code or Codex and are comfortable using recording software, we encourage you to apply. Please briefly describe which of these two common AI tools that you would use for the task.

I need software engineer who can collaborate for AI training works.