AI Ops Engineer – Enterprise AI Platform

About the role

We are looking for an AI Ops Engineer to build the operational backbone for our enterprise AI platforms. The role will enable application teams to release AI products safely, repeatedly and at scale.

Key responsibilities

• Design and maintain CI/CD pipelines and promotion controls for AI applications, agents, platform services and configuration changes across environments.
• Embed LLMOps and AI lifecycle management controls to ensure auditable model releases.
• Implement progressive delivery patterns such as canary releases, controlled roll‑outs and rollback readiness to reduce production risk.
• Integrate AI quality checks, telemetry, dashboards, runbooks and readiness criteria into the delivery lifecycle.
• Provide AI FinOps visibility and governance for model usage, token spend, capacity and quota management.
• Create reusable templates, standards and playbooks that allow teams to self‑service while maintaining enterprise control.

Required profile

• Strong production‑engineering background operating cloud‑native, AI or high‑scale API platforms in an enterprise environment.
• Hands‑on experience with CI/CD, GitHub Actions (or equivalent) and environment management.
• Working knowledge of LLMOps, telemetry, release governance and production‑readiness practices.
• Experience with observability, change control, service reliability and continuous operational improvement.
• Ability to partner with platform engineering, QA/SRE, cybersecurity, architecture, product and delivery teams.

Required skills

• CI/CD pipeline design
• GitHub Actions or equivalent automation
• LLMOps practices
• Telemetry and observability tooling
• Cloud‑native platform operations
• AI model lifecycle management
• Release governance and change control
• Service reliability engineering