MLOps / AI Operations Engineer
Core
Industrialize AI delivery through automated deployment, evaluation operations, observability, reliability engineering, and transparent consumption management.
Role type
Senior MLOps / AI Operations Engineer
Builds
CI/CD pipelines for AI services, prompts, agent configurations, infrastructure, and evaluation assets
Domain
Cloud operations, Generative AI, Agentic Systems
Deliverable
production ML models | infrastructure
Required skills
CI/CD pipeline automation, Infrastructure as Code, container orchestration, observability implementation, model lifecycle management, incident response, cost optimization
Preferred skills
Progressive delivery strategies, secrets management, vulnerability scanning, non-deterministic system reliability practices
Technologies
GitHub Actions, Azure DevOps, GitLab CI, Terraform, Bicep, Docker, Kubernetes, MLflow, OpenTelemetry, LangSmith, Langfuse, Azure Monitor, Prometheus, Grafana
Responsibilities
Build CI/CD pipelines for AI services and agent configurations; Automate environment provisioning, testing, deployment, and rollback; Implement tracing, logging, and operational dashboards; Monitor latency, capacity, token usage, and cost drivers; Define runbooks and manage production support handover
Seniority
Senior, hands-on IC
