Vacature Senior Cloud Engineer AI (Sovereign Lifecycle & Delivery)

Startdatum: 11 mei 2026

Einddatum: 10 mei 2027

Optie op verlenging: ja

Duur: 12 maanden

Sluitingsdatum: 29 april 2026

Publicatiedatum: 23 april 2026

Vacancy

Position: Senior Cloud Engineer AI (Sovereign Lifecycle & Delivery)

Location: Hybride

Employment: Fulltime

Level: Senior

Role Summary

You will ensure that all AI tools in the managed service are production-ready, observable, and governed. You will create the full lifecycle management processes for tools and the required infrastructure within a sovereign environment. You will work with the PO, AI Infrastructure Architects and Sovereign Cloud Engineering teams as part of a scrum team balancing time-to-market, feature development and operations.

Key Responsibilities

• ML Lifecycle & Automation
  • Build CI/CD/CT pipelines for model deployment, data ingestion, embedding generation, and version management.
  • Automate rollout and staged deployments with regulatory-grade auditability.
  • Standardize interfaces between data pipelines, model registries, inference runtimes, and agentic workflows.
• Governance, Compliance & Auditability
  • Implement model lineage, provenance, versioning, and reproducibility controls.
  • Manage an approved model catalogue, including review workflows, validation checkpoints, and compliance checks.
  • Ensure audit trails exist across data pipelines, inference endpoints, and autonomous agent actions.
• Reliability & Observability
  • Build production-grade monitoring, alerting, logging, and analytics across all AI service layers.
  • Ensure high availability, performance tuning, run-time stability, and capacity planning for AI workloads.
  • Implement cost control mechanisms, quota management, and resource governance.
• Operational Excellence
  • Maintain robust runbooks, operational guidelines, and monitoring dashboards for the AI platform.
  • Collaborate with the team to ensure secure and efficient operational environments.
  • Work with AI Engineering on deployment patterns, agent behavior monitoring, and RAG workflow stability.

Experience & Skills

• Strong background in MLOps, DevOps, or data engineering in secure or regulated environments.
• Experience with model registries, observability tools, infrastructure-as-code, and automation.
• Understanding of ML governance, model lifecycle patterns, and production delivery and operations of AI systems.

Wensen:

• Het is een pre als je een sterke achtergrond hebt in ML Ops, DevOps, of data engineering in veilige of gereguleerde omgevingen
• Ervaring met modelregistraties, observability tools, infrastructure-as-code, en automatisering is een pre
• Bij voorkeur begrip van ML governance, model lifecycle patronen, en productie levering en operatie van AI systemen