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

Locatie: Hybride 
Dienstverband: Fulltime
Niveau: Senior
START PER DIRECT (ZSM)

About Atos

At Atos, we accelerate intelligence to help shape a responsible, secure and AI-powered digital future. By bringing together human, collective and artificial intelligence, we empower transformation–with speed, relevance and impact.
From mission-critical environments to sovereign cloud, cybersecurity and AI-driven services, we meet clients where they are and take them where they need to go.
Our technologies are seamless, secure, and built with sustainability at their core. With innovation and intelligence embedded in everything we do, we help our clients, our people and society move forward with confidence in a world that never stops.

Atos Sovereign AI

Atos Sovereign AI is a self‑contained AI ecosystem designed to give organizations full operational independence and resilience in environments where data protection, compliance, and control are critical. It provides a platform built on strict sovereignty principles, maintaining full autonomy and operational control across the entire AI stack.
The offering includes a compliant Platform‑as‑a‑Service combined with specialized AI capabilities such as enterprise search, retrieval‑augmented generation, governed inference, and agentic workflow management. It enables organizations to innovate with AI without relying on hyperscalers, reducing vendor lock‑in and strengthening strategic autonomy. Overall, Atos Sovereign AI empowers critical sectors to embed AI deeply and safely into core business operations.

Senior Cloud Engineer AI (Sovereign Lifecycle & Delivery)

Role Summary

The Senior AI Cloud Engineer ensures that all AI tools in the managed service are production-ready, observable, and governed. This role creates the full lifecycle management process for tools and the required infrastructure within a sovereign environment.
As valued member of the Atos Sovereign AI team in the Cloud & Modern Infrastructure Department you work together with the PO, AI Infrastructure Architects and Sovereign Cloud Engineering teams to extend the Sovereign Cloud with our AI Platform. You become part of a scrum team with strong autonomy, and a strong drive to balance time-to-market and 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 AI platform.
• Collaborate with your 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 ML Ops, 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.