Release Manager (MLOps Delivery Lead)

About the role

DeepLight AI, an AI and data consultancy serving financial services and banking clients in the UAE, is looking for a highly technical Release Manager (MLOps Delivery Lead) in Dubai. The role drives end-to-end technical delivery, release governance and production operations of Data Science and Machine Learning workloads on AWS for tier-one enterprise clients. It combines technical delivery leadership, AWS cloud infrastructure, MLOps, DevSecOps, networking and production change governance.

Key responsibilities

• Lead technical delivery planning and execution of AWS MLOps platform capabilities, model deployments and cloud infrastructure across dev, test and production environments.
• Partner with Data Scientists, Product Owners and business teams to turn analytics algorithms into technical epics, NFRs, deployment roadmaps and acceptance criteria.
• Coordinate AWS account topologies, IAM, compute, storage, container/Kubernetes dependencies, VPC subnets, firewalls, PrivateLink endpoints and DNS.
• Create and manage technical change requests, sequence releases, build CAB evidence packages, coordinate release windows and lead rollback readiness.
• Work with Cybersecurity, Data Privacy and Model Risk Validation teams to meet banking regulations, audit standards and automated CI/CD/CT pipelines.
• Ensure production telemetry covers infrastructure, data quality and model drift, and monitor AWS compute consumption and token spend to optimise costs.

Required profile

• 8+ years of hands-on technology delivery experience managing complex cloud, data platform or machine learning programs in enterprise environments.
• Proven track record of complex production releases with cloud infrastructure, network/firewall updates, change requests, CAB sign-offs and rollback management.
• Experience delivering technical solutions in highly regulated sectors under Model Risk, Cybersecurity and Data Privacy rules.
• Ability to communicate complex technical decisions clearly to high-level stakeholders.

Required skills

• Full ML lifecycle: SageMaker, feature stores, experiment tracking, model registries, inferencing, drift monitoring.
• AWS services: IAM, VPC, ECS/EKS, S3, CloudWatch.
• Terraform, GitHub Actions CI/CD/CT pipelines, Docker/Kubernetes, environment segregation.
• Preferred: AWS Certified Solutions Architect - Professional or AWS Certified Machine Learning - Specialty, and PMP, PRINCE2, SAFe or Agile.

What we offer

• Competitive salary.
• Personal health insurance and individual visa sponsorship.
• Professional development and certification support, subscription reimbursement, monthly employee incentive program.
• Career advancement opportunities.