AI/Agentic Engineer

The Calibration team automates the calibration of our quantum processors so they remain performant and operate correctly. We're building a system to automate calibration end-to-end, with the ambition of moving toward an agentic approach able to detect and self-correct edge cases, rather than requiring human intervention at every anomaly. As Software Engineer, Calibration Automation, you'll design and build this system, taking it from proof of concept to a production-grade, deployable product over the coming months, working closely with the experimentalists and software engineers of the bring-up team.

Design and build LLM-based agentic systems that run calibration on the chip, or supervise/monitor the execution of existing automations, depending on the deployment mode.
Design and build AI-based tools to ease the development and improvement of automation routines.
Work toward a system able to detect, handle, and eventually self-correct edge cases - situations where calibration doesn't go as expected - leveraging LLM-driven reasoning over experimental data to reduce the need for human intervention.
Take the project from proof of concept to a robust, deployable product once the architecture is stabilized.
Ensure calibration automations are reproducible, observable and maintainable — build the pipelines, monitoring and logging needed to trust the system in production.
Build the engineering fundamentals a production agentic system needs: tool integration, state management, error handling, rollback, and guardrails.
Integrate the system with the team's existing Python codebase, CI/CD and automation framework, working closely with the wider engineering team on infrastructure choices.

5-6 years of experience in a senior software engineering role.
Strong, hands-on experience building with LLMs and agentic architectures (e.g. LangGraph, AutoGen, CrewAI) - designing agent loops, tool calling, memory/state management, and evaluation.
Confirmed, production-level Python software experience, including running systems reliably in production (not just experimentation).
Proven ability to take a proof of concept to a stable, deployable product once the architecture is validated.
Comfortable working with numerical/scientific data to inform decision-making in an automated system.
Strong analytical and communication skills, with the ability to work with both technical and experimental/research teams.
Fluent English; French is a plus.

Screening call with Alex (30 min)
Hiring Manager interview (45 min)
Technical onsite Interview (90 min)
Leadership Interview (30 min)
Fit Interview (30 min)