AI Developer – Agentic AI
Indexed description
Job Type: Full-Time (Contract-to-Hire)
Location: Hybrid/Onsite – Minnesota
Send resumes to: [email protected]
More roles: www.irow9.com/careers
Summary
Hands-on AI Developer building production-grade Agentic AI and RAG solutions for an enterprise AI platform. Strong experience with LangGraph/LangChain, multi-agent orchestration, Python/FastAPI, and LLM evaluation is required. Azure experience is a plus, but strong AI engineering experience on any cloud is considered.
Responsibilities
- Build and maintain end-to-end production RAG pipelines, including ingestion, parsing, chunking, embeddings, vector/hybrid search, reranking, grounding, and citations.
- Develop multi-agent systems using supervisor/specialist patterns, tool calling, agent state, and agent-to-agent communication.
- Build and govern MCP tool contracts for retrieval and operational data.
- Develop LLM evaluation and quality frameworks, including prompt versioning, regression testing, retrieval/answer evaluation, and hallucination control.
- Design async Python/FastAPI services with OpenAPI-native APIs for AI, agent, and retrieval capabilities.
- Build AI-powered user experiences using React/Next.js and TypeScript.
- Integrate enterprise data sources including Microsoft Graph, SharePoint, HRIS/LMS platforms.
- Deliver working software through weekly demos and milestone-driven development.
- Build and deploy containerized services using technologies such as PostgreSQL and Redis.
- 4–6 years of hands-on software engineering experience, including 2–3 years building LLM/Agentic AI solutions.
- Proven experience shipping production RAG systems with real users and real retrieval-quality challenges.
- Strong, code-level experience with LangGraph, LangChain, AutoGen, Microsoft Agent Framework, Semantic Kernel, CrewAI, or comparable agent frameworks.
- Strong Python development skills with FastAPI, async programming, and API design.
- Experience with RAG, embeddings, vector stores, hybrid search, semantic reranking, grounding, and citations.
- Experience with LLM prompt engineering, structured outputs, evaluation, and quality control.
- Ability to work independently, learn rapidly, adapt to new AI frameworks/models, and deliver production software.
- Working proficiency with React/Next.js and TypeScript.
- Azure AI: Azure OpenAI, Azure AI Search, Azure AI Foundry, Container Apps, Entra ID/MSAL.
- Experience with vector technologies such as pgvector, FAISS, Pinecone, Azure AI Search, or similar.
- Experience with RAGAS or comparable evaluation frameworks.
- Experience with PostgreSQL, Redis, and containerized deployments.
- Experience delivering Agentic AI solutions specifically on Azure.
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