Lead DevOps Engineer (AI & GPU)
Core
Own the delivery, model-serving, routing, and observability layer of AI-native platforms, ensuring AI workloads are shippable, economical, and fully visible across cloud, on-prem, edge, and air-gapped environments.
Role type
Senior IC DevOps/MLOps Engineer (AI & GPU)
Builds
AI-native platform runtime, CI/CD/CV pipelines, model serving infrastructure, and observability stacks
Domain
AI/ML Infrastructure, Cloud-Native Systems, GPU Computing
Deliverable
production ML models
Required skills
CI/CD/CV pipeline design, GitOps, GPU model serving (Ray, vLLM, Triton), OpenTelemetry, FinOps, API gateway/routing, artifact governance
Preferred skills
LLM evaluation/debugging, sandboxed execution, GPU telemetry optimization, lineage contracts
Technologies
ArgoCD, Helm, GitHub Actions, Ray Serve, vLLM, Triton, NIM, Prometheus, Grafana, Loki, Tempo, Jaeger, LangSmith, Envoy, OpenCost, Kubecost, Trivy, MLflow, Harbor
Responsibilities
Build and operate CI/CD/CV pipelines for AI services and agents; Manage governance, discovery, and license tracking for AI assets; Implement resource quotas, rate limits, and cost attribution; Operate full observability stacks (metrics, logs, traces, LLM debugging); Automate GitOps-based delivery with quality gates; Close the loop between telemetry and deployment decisions.
Seniority
Senior, hands-on IC