AI Engineer
Summary
Build and deploy AI-powered applications like RAG systems and chatbots using Python, LangChain, and Azure AI services.
We are hiring a hands-on AI Developer to build intelligent, production-ready AI solutions across a variety of domains — from document processing and data extraction to conversational AI and automated report generation. You will work directly with clients and internal teams to deliver high-quality AI-powered applications.
- 3–6 years of software development experience with 2+ years focused on AI/GenAI solutions.
- Strong 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 environments.
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.