Cloud exposure preferred (Azure/AKS, managed services), with bonus experience in performance tuning, frontend collaboration, and model governance/monitoring. • Design and develop Python-based APIs and microservices (FastAPI, async patterns) and agentic AI workflows using LangChain/LangGraph.
Numbers & Facts
Location
Cary, NC
Salary
$110,000–$130,000 Per Year
Description
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.
• 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.
• 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.