Cloud Native GenAI Engineer - Technical Architect

Role Overview:

Architects, deploys, and scales production-grade Generative AI applications and autonomous agents. Bridges AI modeling and distributed systems engineering using cloud-native patterns, microservices, and Kubernetes.

Key Responsibilities

• Model Serving & Kubernetes: Deploy open-weights models (vLLM, TensorRT-LLM) on Kubernetes (EKS/GKE/AKS) with GPU autoscaling and latency optimization.
• Vector & RAG Pipelines: Build high-throughput retrieval architectures using vector databases (Qdrant, Milvus, Pinecone, pgvector) and streaming data pipelines.
• Agentic Orchestration: Develop multi-agent workflows (LangGraph, CrewAI) and integrate external tool calling protocols (MCP).
• LLMOps & Governance: Set up tracing (LangSmith, OpenTelemetry), guardrails (NeMo Guardrails), and FinOps token budget controls.

Core Skill Requirements

• Infrastructure: Kubernetes, Docker, Terraform, AWS/GCP/Azure.
• Languages & Frameworks: Python (FastAPI), Go or TypeScript, LangChain/LangGraph, LlamaIndex, PyTorch/Hugging Face.
• Data & Inference: Vector DBs, vLLM/Ollama, Kafka, PostgreSQL.