Java Technical Lead

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. Roles & Responsibilities 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.

Must Have Technical/Functional Skills 13+ years of experience with IT 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., Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring.