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Alice & Bob

superconducting quantum computing · cat qubits

Head of IT and AI Ops

France · HybridPosted 2 months ago
InfrastructureStaff+Cdi
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About the role

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10+ years of experience in a relevant technological field, with demonstrated experience managing managers and structuring multi-team organizations.

Strong IT operations foundation: identity and access management, endpoint lifecycle, SaaS stack administration, support operations, vendor management, and security controls at scale.

Solid Cloud & Infrastructure Operations background: multi-cloud architecture and cost governance, infrastructure-as-code, container orchestration, network and storage management, reliability engineering, and capacity planning across production and research environments.

Hands-on Cybersecurity expertise: threat detection and incident response, vulnerability management, security architecture review, compliance frameworks, data protection controls, and embedding security practices across engineering and operational workflows.

Proven MLOps or ML infrastructure experience: reproducible pipelines, experiment tracking, data and model versioning, CI/CD for ML workflows, and observability in research and engineering environments.

Ability to operate across a technically diverse organization: PhD-level researchers, hardware engineers, software engineers, and business stakeholders. You are comfortable with ambiguity, but you do not let ambiguity become chaos: you create structure, make trade-offs explicit, and drive decisions.

Strong execution discipline: roadmap ownership, budget management, prioritization under constraint, measurable delivery. You can zoom out to define strategy and zoom in to debug a process, challenge an architecture, or unblock a team.

You combine a strong service mindset with the ability to enforce standards. You care deeply about user experience, and you know when pragmatism must give way to rigor.

Fluent in French & English.

Nice to have:

Experience in deeptech, quantum, semiconductor, aerospace, HPC, or another R&D-intensive hardware environment.

Experience supporting scientific computing environments: GPU/CPU clusters, SLURM, Kubernetes, distributed systems.

Experience managing IT operations across multiple sites.

Experience with AI tooling governance and secure adoption of LLM tools within a technical organization.

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