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About the role
The Workflow team leverages software, AI and automation to improve the efficiency of the R&D processes of Alice & Bob.
As a Senior Applied AI Engineer in this team, you will design, deliver, and maintain high-quality, scalable and robust AI-based solutions to solve complex problems encountered by R&D teams and improve their efficiency. You’ll act as an individual contributor and technical leader to key projects dealing with both simulation and real-life execution of quantum experiments. You’ll work with elite researchers and engineers across Alice & Bob.
You don’t need to be a physics expert to succeed in this position. If you’re curious, motivated, and a fast learner, we’ll teach you everything you need to communicate efficiently with our scientists, and make a positive impact through your work.
Responsibilities
- Lead projects from conception to delivery autonomously, navigating ambiguity while meeting timelines.
- Own the design, development, maintenance, and delivery of AI-powered features, tools, or workflows, in partnership with Software Engineers.
- Evaluate, benchmark, and deploy LLMs and agentic AI systems for R&D use cases, selecting appropriate models, architectures, and evaluation methodologies.
- Implement and promote best practices in LLMOps and DevOps (e.g., model versioning, evaluation pipelines, CI/CD, observability, infrastructure as code).
- Lead design and code reviews for AI-related projects, and provide actionable feedback to peers.
- Collaborate efficiently with colleagues of various backgrounds (researchers, engineers, product managers…) to deeply understand their needs and proactively suggest AI-based workflows to make them more efficient.
- Mentor and support more junior engineers in their technical growth and onboarding.
- Participate in the continuous improvement of the team's processes.
Requirements
- 5+ years of professional software engineering experience, including at least 2 years focused on AI/ML systems in production environments (LLMs, agentic pipelines, RAG, or similar).
- Strong software engineering skills, with a track record of shipping reliable, maintainable code in a team setting (code reviews, CI/CD, testing, observability).
- Hands-on experience evaluating, fine-tuning, and deploying LLMs (prompt engineering, evaluation frameworks, and model selection).
- Familiarity with LLMOps practices: model versioning, evaluation pipelines, monitoring/tracing in production.
- Ability to communicate and work efficiently with colleagues from various backgrounds (researchers, engineers, product managers), and to translate their needs into actionable technical items.
- Professional-level English proficiency, both written and spoken.
Nice to have
- Experience working in a scientific or R&D-heavy organization.
- Experience with agentic AI frameworks (e.g., LangChain).
- Exposure to workflow automation tools or data pipelines (e.g., Airflow, Prefect).
- Experience with infrastructure-as-code and a cloud platform (e.g., AWS, GCP, Azure).
Recruitment Process
Screening call with Doriane (30 min)
Hiring Manager Interview (45 min)
Technical Interview with the Team (60 min)
Leadership Interview (30 min)…
