AI Engineer Lead (7+)
· 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
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