• Design and develop backend microservices in Python (Django, Flask, or FastAPI) powering GenAI applications and internal automation platforms. • Integrate with LLM APIs (OpenAI, Anthropic) and implement RAG pipelines using vector databases such as Pinecone or Chroma to enhance contextual intelligence. • Develop AI workflow orchestration — prompt routing, retrieval logic, tool execution, memory handling, and multi-agent collaboration — using LangChain and LangGraph. • Build APIs and backend modules that connect to financial systems, credit decision engines, and customer experience platforms. • Manage structured and unstructured data pipelines, integrating with PostgreSQL, MongoDB, and data lakes. • Deploy and maintain services using Docker and cloud environments (Azure or AWS), ensuring scalability, performance, and security compliance. • Collaborate with cross-functional teams in the US and Europe, including frontend, DevOps, and data science units, to deliver production-grade AI capabilities.