Release Manager

About DeepLight AI

The opportunity

What you'll do

• Lead delivery of AWS MLOps capabilities, model deployments, and supporting infrastructure across development, test, and production environments.
• Translate data science requirements into technical epics, non-functional requirements, deployment roadmaps, and acceptance criteria.
• Coordinate AWS accounts, IAM, compute, storage, containers, Kubernetes, VPC subnets, firewalls, PrivateLink, and DNS across cloud teams.
• Manage change requests, release sequencing, CAB evidence, release windows, and rollback readiness.
• Work with cybersecurity, data privacy, and model risk teams to maintain regulatory and audit compliance and CI/CD/CT controls.
• Ensure production telemetry covers infrastructure, data quality, and model drift; monitor AWS compute and token costs.
• Build stakeholder trust, explain technical decisions, and present solutions and delivery plans.

What we're looking for

• At least 8 years of hands-on technology delivery experience managing complex cloud, data platform, or machine learning programs in enterprise environments.
• Proven experience planning production releases involving infrastructure, network or firewall updates, change requests, CAB approvals, and rollback management.
• Strong understanding of the ML lifecycle, including SageMaker, feature stores, experiment tracking, model registries, inferencing, and drift monitoring.
• Strong understanding of AWS IAM, VPC, ECS/EKS, S3, and CloudWatch.
• Practical knowledge of Terraform, CI/CD/CT pipelines, GitHub Actions, Docker or Kubernetes, and environment segregation.
• Direct experience delivering technical solutions in highly regulated sectors with Model Risk, Cybersecurity, and Data Privacy requirements.

Additional advantages

• Financial services, banking, or capital markets experience releasing data platforms or AI models is an advantage.
• AWS Certified Solutions Architect - Professional or AWS Certified Machine Learning - Specialty is an advantage.
• PMP, PRINCE2, SAFe, or Agile credentials backed by technical delivery experience are an advantage.

Benefits

• Benefits include health insurance, visa sponsorship, professional development and certification support, role-related subscription reimbursement, and a monthly employee incentive program.
• The employer describes opportunities to work on AI projects and pursue career advancement.