Senior MLOps Engineer
Core
Build and productize AI capabilities (RAG pipelines, model serving) into a self-service platform for business units using Databricks and Kubernetes.
Role type
Senior MLOps Engineer (Platform Engineering)
Builds
Scalable, governed, and developer-friendly AI services and the Agentic Platform runtime.
Domain
Enterprise AI / MLOps / Cloud Infrastructure
Deliverable
production ML models
Required skills
MLOps/SRE, Databricks MLflow, CI/CD, Infrastructure as Code (Terraform/CrossPlane), Cloud Networking (Azure/AWS), Model Evaluation & Monitoring, SLO Management, Incident Response, Cost Optimization, Kubernetes/Seldon, Unity Catalog.
Preferred skills
Agentic AI evaluation patterns, RAG observability, Multi-cloud operations, Cross-region latency management.
Technologies
Databricks, MLflow, Mosaic, Kubernetes, Seldon, Azure, AWS, Terraform, CrossPlane, ArgoCD, Istio, Knative, Opensearch, Prometheus, Grafana, Unity Catalog.
Responsibilities
Define reference MLOps stack and CI/CD patterns; Standardize serving topologies (Databricks vs Kubernetes); Implement evaluation and monitoring; Integrate governance-by-design (Unity Catalog); Operate the Agentic Platform to SLOs.
Seniority
Senior, hands-on IC