Summary
✨ AI‑Generated
An organization is seeking an AI operations engineer to create reliable AI delivery processes, automate deployments, manage AI lifecycles, and improve production readiness for advanced platforms.
Highlights
Build operational foundations for AI platforms, improve deployment reliability, and establish scalable practices for AI delivery teams.
Description
Role Purpose
We are seeking an AI Ops Engineer to establish the operational backbone for enterprise AI platforms, enabling application teams to release AI products safely, repeatedly, and at scale.
The role is accountable for production release discipline, LLMOps practices, deployment automation, operational governance, cost visibility, and self-service operating standards for AI-native delivery teams.
Key Responsibilities
AI Release Engineering & CI/CD: build and design standard release pipelines and promotion controls for AI applications, agents, platform services, and configuration changes across environments, ensuring repeatable deployment, governance, and release evidence.
LLMOps & AI Lifecycle Management: embed operating controls for models, AI assetsand release for auditable.
Progressive Delivery: Implement deployment patterns to reduce production risk, including controlled rollout, canary release, and rollback readiness Evaluation, Observability & Production Readiness: Embed AI quality checks, operational telemetry, dashboards, runbooks, and readiness criteria into the delivery lifecycle so AI services are measurable and supportable.
AI FinOps & Capacity Governance: Provide visibility and controls for AI workload consumption, including model usage, token spend, platform capacity, quota management, and optimization opportunities.
Self-Service & Continuous Improvement: Convert proven operating patterns into reusable templates, release standards, onboarding guidance, operational playbooks, and paved-road workflows that allow teams to move quickly while maintaining enterprise control.
Required Experience
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 automation, 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 to standardize safe and scalable AI operations.
AI Ops Engineer in Abu Dhabi, United Arab Emirates
