| Job Location | Abu Dhabi, UAE |
| Education | Not Mentioned |
| Salary | Not Mentioned |
| Industry | Not Mentioned |
| Functional Area | Not Mentioned |
Operationalizes AI: deployment, monitoring, cost, and governance for models and LLM applications running in production. What you'll doBuild CI/CD pipelines for model and LLM application deployment Stand up model monitoring, versioning, and rollback systems Manage cost, latency, and reliability of production AI workloads Implement governance controls: access management, audit logging, usage tracking Partner with the security team on AI-specific compliance requirements Support multi-cloud AI infrastructure across AWS, Azure, and GCPSkillsWhat you bring4+ years in DevOps or platform engineering, including 1?2+ years specific to ML/AI systems Experience with Kubernetes, Docker, and Terraform or an equivalent infrastructure-as-code tool Familiarity with MLOps tooling such as MLflow, Kubeflow, SageMaker, or Vertex AI Strong scripting ability in Python or Go, with CI/CD pipeline experience Working understanding of model versioning, monitoring, and cost optimization practices Nice to haveExperience with LLM-specific observability tools such as LangSmith or Arize AWS, Azure, or GCP cloud certification
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