AI Ops Engineer

About the role

We are seeking an AI Ops Engineer to build the operational backbone for enterprise AI platforms, enabling application teams to release AI products safely, repeatedly, and at scale.

Key responsibilities

• Build standard release pipelines and promotion controls for AI applications, agents, platform services, and configuration changes.
• Ensure repeatable deployments with appropriate governance and release evidence.
• Implement controlled rollout, canary release, and rollback‑readiness practices to reduce production risk.
• Embed operating controls for models and AI assets to support auditability and AI lifecycle management.
• Integrate AI quality checks, operational telemetry, dashboards, runbooks, and production‑readiness criteria into delivery processes.
• Establish reusable operational standards and practices for AI‑native teams.
• Provide visibility into AI workload consumption, including model usage, token spend, platform capacity, quota management and optimisation opportunities.
• Convert proven operating patterns into reusable templates, release standards, onboarding guidance and operational playbooks.

Required profile

• 7+ years of relevant experience in production engineering for cloud‑native, AI or high‑scale API platforms.
• Hands‑on experience with CI/CD, GitHub Actions or equivalent automation and environment management.
• Working knowledge of LLMOps, telemetry, release governance and production readiness.
• Experience with observability, change control, service reliability and continuous operational improvement.
• Ability to collaborate with Platform Engineering, QA/SRE, Cybersecurity, Architecture, Product and Delivery teams.

Required skills

• CI/CD
• GitHub Actions
• LLMOps
• Telemetry
• Release governance
• Production readiness
• Observability
• Change control
• Service reliability
• Cloud‑native platforms
• AI platforms
• High‑scale API platforms