Key Responsibilities
Develop and deploy AI solutions including RAG systems, chatbots, document intelligence pipelines, and structured data extraction workflows.
Build backend services and APIs using Python and FastAPI, with well documented Swagger/OpenAPI specifications.
Implement LangChain and LangGraph-based agentic workflows; instrument and evaluate them using LangSmith.
Integrate Azure services
Azure Document Intelligence, Azure AI Search, and Azure-hosted LLMs
into production pipelines.
Work with Microsoft Foundry for AI application development and deployment.
Interact with clients to understand requirements, provide updates, and participate in solution walkthroughs and demos.
Write clean, maintainable, and well-tested code; participate in code reviews.
Troubleshoot, optimize, and continuously improve deployed AI solutions.

Required Skills & Experience
6 years of software development experience with 3+ years focused on AI/GenAI solutions.




Solid Python development skills; experience building APIs with FastAPI.
Hands-on experience with LangChain and LangGraph for building LLM-powered applications.
Practical experience with RAG (Retrieval-Augmented Generation) architectures and vector/semantic search.
Familiarity with Azure Document Intelligence and Azure AI Search.
Experience with Microsoft Foundry or similar AI development platforms.
Solid understanding of REST APIs, Swagger/OpenAPI documentation, and JSON data handling.
Ability to communicate effectively with clients and articulate technical concepts clearly.

Nice to Have
Experience with structured/unstructured data extraction projects (invoices, contracts, reports, tables).
Exposure to document generation pipelines using AI.
Familiarity with LangSmith for observability, tracing, and evaluation of LLM applications.
Experience working in Agile/Scrum delivery settings.

📌 Ai Developer Noida
🏢 Fenebris India
📍 Noida