Lead DevOps and MLOps engineering for AI workloads at scale, owning CI/CD/CV pipelines, model-serving infrastructure (Ray, vLLM, Triton, NIM on GPUs), and a full observability stack (Prometheus, Grafana, Loki, Tempo, OpenTelemetry). Design and operate governance systems for AI assets (MLflow, Artifactory, Harbor, Trivy), cost attribution (Apptio, OpenCost, Kubecost), and FinOps controls; ensure every AI workload is delivered repeatably, traced end-to-end, cost-bounded per tenant, and policy-compliant by default.… Requires 8+ years in DevOps/MLOps/platform engineering with hands-on production ownership of AI or high-throughput services, and deep expertise in model-serving frameworks and observability tooling.
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