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