AI Developer – Agentic AI

Hands-on AI Developer building production-grade Agentic AI and RAG solutions for an enterprise AI platform. Strong experience with Lang Graph/Lang Chain, 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.

• 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 Type Script.
• 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 Lang Graph, Lang Chain, Auto Gen, 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 Type Script.

• 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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