AI Engineer Lead

· 8+ years in ML/AI engineering or DevOps (incl. 4+ yrs production MLOps)

· Education: Master's (preferred) or Bachelor's in CS, Software Engineering, or Data Science

· About the Role Own the complete MLOps backbone for AI/ML and GenAI solutions — from model packaging and CI/CD delivery through production monitoring. Bridge data-science experimentation and enterprise-scale deployment, and set engineering standards for the Enterprise AI MLOps practice. Key Responsibilities

· Design end-to-end pipelines — ingestion, training, evaluation, packaging, versioning, deployment, and monitoring.

· Own Jenkins CI/CD (Declarative/Scripted) for Dev → QA → Production with multi-stage gates.

· Deploy model-serving APIs on AKS (FastAPI, vLLM); apply ONNX/TensorRT and blue/green rollouts.

· Build observability stacks — drift detection (Evidently AI), Prometheus/Grafana, Azure Monitor.

· Enforce DevSecOps — zero-credential pipelines via Key Vault + Managed Identity, SonarQube, Trivy/Snyk.

· Set MLOps engineering standards and mentor engineers across the practice