Responsibilities

• Design, build and deploy Generative AI and Agentic AI solutions from prototype to production
• Implement multi-agent orchestration patterns using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel or OpenAI Agents SDK
• Develop the orchestration backbone for advanced workflows including planning, checkpointing, retries, fallback handling and resumption of long-running processes
• Build and optimize RAG pipelines, including chunking strategies, embeddings, vector/hybrid search and retrieval evaluation with grounded responses and citations
• Develop memory and context management solutions, including short-term and long-term stores and compaction strategies
• Write robust Python APIs and services (e.g., FastAPI), incorporating async execution, background jobs and containerized deployments
• Integrate enterprise systems and tools using protocols such as MCP, A2A, OpenAPI, REST and gRPC, ensuring graceful degradation and retries
• Apply enterprise security and governance practices including RBAC, prompt safety checks, traceability and secrets management
• Implement evaluation pipelines and observability frameworks using tools such as Langfuse, Arize or OpenTelemetry
• Contribute to architectural design decisions, code reviews and engineering standards for platform development