- 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 strong 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.