AI Ops Lead
Quandela
AI Ops Lead
Quandela
Photonic quantum computers and single-photon sources
Quandela · Massy, France (Hybrid) · Full-time · Posted 2026-11-13
Workplace: hybrid
Department: Operations
Quandela is a global leader in quantum computing, designing, building, and delivering cutting-edge quantum solutions for research and industry. Its offerings include energy-efficient quantum computers for data centers, full-stack quantum computing solutions accessible via the cloud, and algorithm access services for academic and industrial customers. Following a pragmatic, step-by-step roadmap, Quandela has been deploying industrial-grade systems since 2023 while developing future generations of fault-tolerant quantum computers capable of scaling through the integration of thousands of photonic components. Quandela is committed to making quantum computing accessible to all in order to address the most complex industrial and societal challenges.
Learn more at: Quandela | Leading Photonic Quantum Computing Solutions
About this position
You’ll be in charge of building and leading Quandela’s AI Ops Department, under the supervision of the COO.
You’ll be designing a robust, resilient and safe AI architecture at the company level, but you will also work a lot alongside the different departments (legal, finance, business, hardware and software engineering) in order to understand their workflows and to implement solutions.
You will share the ownership of this architecture with the IT Manager, who will be responsible for the foundations of the platform (access, devices, data safety…).
You will also be responsible for animating the Quandela AI community, a network of early-adopters championing AI within their teams, by organizing workshops and learning sessions for Quandelians.
Your key responsibilities
· Build and run the internal AI platform: select and integrate the stack (model providers and gateway, approved assistants, retrieval over internal knowledge, evaluation and observability), own the catalogue of approved AI tools, their configuration and their cost, with the IT Manager
· Deliver automations and agents with the teams: collect needs, qualify use cases by impact, feasibility and risk, build workflows and agents
· Drive adoption and skills: animate the network of AI champions, design and run the training program (AI literacy for everyone, role-based sessions, office hours), set up self-service tools so that non-technical teams build and own their own agents
· Own the safety of the system: clear definition of a data access hierarchy, solutions for sensitive data, guardrails for coding agents...
A completed Master’s degree or higher (French Master 2 / Bac+5, an engineering degree conferring the master’s grade, or an equivalent international qualification) in Artificial Intelligence, Machine Learning, Computer Science, Data Science or Applied Mathematics, with strong foundations in software engineering and applied AI.
Examples of relevant European programmes include the M2 Mathématiques, Vision, Apprentissage (MVA) led by ENS Paris-Saclay; the Master’s programmes in Data Science at ETH Zurich and EPFL; the MSc in Machine Learning at UCL; and the MSc in Computing (Artificial Intelligence and Machine Learning) at Imperial College London. These examples are indicative and non-exclusive; equivalent master’s-level programmes are welcome.
5+ years of experience in software engineering, automation, data engineering or technical product roles. Evidence of personally delivering and maintaining solutions used by teams is essential.
A track record of delivering LLM-based automations, including API integrations and workflow platforms such as n8n or Make. Experience taking solutions beyond the proof-of-concept stage and addressing real-world quality, reliability and cost issues.
Ability to write and maintain integration code in Python or JavaScript/TypeScript, and work with APIs and webhooks.
Working knowledge of retrieval-augmented generation (RAG), evaluation, observability and security for LLM systems. An understanding of context management, knowledge-source quality and permission-aware retrieval.
A product mindset: you keep solutions simple and practical while delivering operational improvements. You can prioritise competing requests and translate business or R&D needs into achievable technical solutions.
Proven ability to lead a community of champions (i.e. early adopters) and manage change across a technically diverse organisation, from PhD researchers to business teams.
Strong data discipline, with the ability to classify data before automating processes, document key decisions and workflows, and measure outcomes.
Professional proficiency in French and English.
On-site presence at least three days per week, with occasional travel between sites (Massy, Palaiseau, Paris, Munich, and our other international subsidiaries).
Nice to have
Experience in deeptech: quantum computing, semiconductors, aerospace, HPC or another R&D-intensive hardware environment.
A PhD in AI, Machine Learning, Computer Science or a related scientific field, particularly with applied work supporting research or engineering teams. A PhD is an asset, not a requirement.
MLOps or ML infrastructure experience, including pipelines and versioning.
Familiarity with the EU AI Act, CNIL guidance on generative AI at work and ISO 27001.
Experience governing coding agents in continuous integration.
Experience building a new technical function, mentoring colleagues or coordinating specialist providers.
Competitive salary, flexible based on your experience and expectations
Company savings plan
Process:
Beyond That:
At Quandela, we value scientific curiosity, experimentation and collaboration. If you're passionate about quantum optics, spin physics and quantum technologies, we'd love to hear from you, even if you don't meet every listed requirement.
If you're excited by the challenge of turning scientific ideas into demonstrations, advancing the building blocks of future quantum computing systems and working alongside physicists, engineers and theorists, let's talk.
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Quandela builds full-stack photonic quantum computers in France, including on-premises MosaiQ hardware and cloud access to its processors. It uses semiconductor quantum-dot single-photon sources to create bright, indistinguishable photons that act as optical qubits, with Perceval, an open-source Python framework, for simulating and programming photonic circuits, and Prometheus, a standalone single-photon source for research labs. The company differentiates itself by offering end-to-end hardware, software, and services—from production in its own facilities to cloud access and an acceleration program that guides clients from use-case exploration to hardware delivery. Its goal is to help clients achieve practical quantum advantages across industries such as cybersecurity, energy, finance, logistics, chemistry, and pharmaceuticals.
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