- Build and Productionize cloud native backend services and AI/LLM inference pipelines.

- Design and develop Python-based APIs and microservices (FastAPI, async patterns) and agentic AI workflows using LangChain/LangGraph.

- Implement and optimize LLM capabilities including embeddings, RAG, vector search, prompt/context engineering, and model versioning.

- Package, serve, and monitor models for real-time and batch inference, ensuring operational readiness and performance.

- Build event driven, resilient integrations and containerized services, with hands-on Kubernetes debugging and Helm-based deployments.

- Establish observability, SLOs, CI/CD automation, testing

- Apply solid systems design principles (concurrency, caching, reliability, rate limiting) and robust data engineering practices.

- Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring.

📌 Generative AI Engineer (Pune)
🏢 Tata Consultancy Services
📍 Pune