At a Glance
- Tasks: Build AI agents for preventive health, transforming clinical data into actionable insights.
- Company: Lucis, a pioneering company focused on preventive healthcare and human longevity.
- Benefits: Competitive salary, relocation support, and a collaborative work environment in Paris.
- Other info: Fast-paced culture that values ownership, feedback, and continuous improvement.
- Why this job: Join us to revolutionise healthcare and make a real difference in people's lives.
- Qualifications: 8+ years in software and ML systems, with hands-on experience in AI production.
The predicted salary is between 80000 - 100000 € per year.
Making preventive health the default for every human in Europe.
The mission at Lucis is to believe healthcare should be preventive, not reactive. We’re building the OS for human longevity to help people add more healthy years to their lives.
The role involves building AI agents that act as a doctor for preventive health — analysing 110+ biomarkers, reasoning over clinical data, and delivering protocols that change how people age. The system works, and now we need to make it smarter, faster, and ready for millions of users. As our AI Engineer, you own the reasoning engine: the agents, the retrieval pipelines, the clinical workflows, and the infrastructure that makes it all reliable in production. You work directly with our medical team to translate clinical knowledge into systems that behave like they understand it. This isn’t a research role; it’s a build role. The gap between a great LLM demo and a trustworthy AI doctor is enormous — your job is to close it.
You could be responsible for:
- AI agent architecture — design and ship the multi-agent system behind our AI doctor: reasoning, planning, tool use, clinical citation, and safe fallback behaviour.
- Retrieval & knowledge — vector infrastructure, embedding pipelines, RAG architecture over clinical literature and user health data. You know the difference between retrieval that works and retrieval that a clinician would trust.
- Data pipelines — ingestion and normalisation from labs (Eurofins, Randox), wearables, and third-party partners. Clean data in, reliable inference out.
- Production reliability — LLM endpoints that reason correctly at scale, with observability, evals, and failure modes you’ve thought through before they happen.
- Medical collaboration — translate complex clinical requirements into agent workflows, working side by side with our medical advisors. You don’t need to be a doctor, but you need to earn their trust.
About You:
You’re passionate about the future of human health and want your work to help people stay healthy for longer. You move quickly from idea to execution, take full ownership of what you build, and work best with talented people who care as much as you do. You thrive in fast-moving environments, learn by doing, and value feedback as a way to continuously improve.
You’ll fit in well if:
- You have 8+ years’ experience building and shipping software and ML systems in production.
- You’ve shipped AI agents in production recently — not as a side project, as the core product.
- You think in systems: prompts, retrieval, tool orchestration, evals, and failure modes are all part of the same design problem.
- You’re hands-on with vector databases, retrieval pipelines, and LLM endpoints — Python-native, comfortable in LangChain or equivalent.
- You write evals before you ship, because you know that vibes-based QA doesn’t work for clinical reasoning.
- You’ve worked with messy real-world data (health, finance, legal) and built pipelines that handle it without breaking silently.
- You’re genuinely obsessed with health — you track your own biomarkers, read PubMed, or are just deeply frustrated that healthcare is still reactive.
We might not be a fit if:
- You need a clearly defined role with stable responsibilities.
- You prefer strategic advisory work over hands-on execution.
- You’ve only worked in large, well-established companies.
- You need perfect information before making decisions.
- You prioritise predictable 9-5 work over mission intensity.
- You’re uncomfortable with frequent context-switching and urgent pivots.
Our current stack includes:
- Python repo and TS monorepo (platform)
- PostgreSQL + Prisma
- AWS (Terraform)
- GitHub Actions
- Claude Code + Cursor AI/agent framework: mostly Langchain ecosystem
The process includes:
- Intro call (20 min): culture & role fit.
- Technical interview (30 min).
- At-home case study: hands-on project, delivery in 2 days.
- Deep dive (90 min) and team chat (on-site).
- Reference calls.
How We Work:
We work together from our Paris hub. We’re passionate about what we’re building and believe the fastest way to create something exceptional is side by side. We’re open to relocation support for the right individuals, and we welcome missionaries who travel to work with us in Paris on a regular basis.
Rigor without ego: Audits, science, and code all deserve the same high bar.
Radical ownership: Feedback loops are short; everyone contributes to building the best version of Lucis.
Velocity over perfection: We ship daily and prefer a good decision today over a perfect one next week.
At Lucis, AI isn’t just our product, it’s our engine. 100% of our teams are equipped with the best AI agents. You have carte blanche to explore and automate everything that can be, so you can focus exclusively on high-value work.
AI engineer employer: Lucis (YC P25)
At Lucis, we are dedicated to revolutionising healthcare through preventive measures, and as an AI Engineer in our Paris hub, you will be at the forefront of this mission. Our vibrant work culture fosters collaboration and innovation, providing you with ample opportunities for professional growth while working alongside passionate individuals who share your commitment to improving human health. With a focus on rapid execution and radical ownership, you'll have the freedom to explore and implement cutting-edge AI solutions that truly make a difference in people's lives.
StudySmarter Expert Advice🤫
We think this is how you could land AI engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and healthcare. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and understanding of clinical workflows. Be ready to discuss how you can contribute to making preventive health the default for everyone!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our mission at Lucis.
We think you need these skills to ace AI engineer
Some tips for your application 🫡
Show Your Passion for Health:Let us see your enthusiasm for preventive health in your application. Share any personal experiences or projects that highlight your commitment to making healthcare better. We love candidates who are genuinely obsessed with health!
Be Clear and Concise:When writing your application, keep it straightforward. We appreciate clarity over fluff. Make sure to highlight your relevant experience and skills that align with the role of AI Engineer without going off on tangents.
Tailor Your Application:Don’t just send a generic application! Customise your CV and cover letter to reflect how your background fits our mission at Lucis. Mention specific technologies or methodologies you’ve used that relate to the job description.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Lucis (YC P25)
✨Understand the Mission
Before your interview, dive deep into Lucis' mission of making preventive health the default for everyone in Europe. Familiarise yourself with their approach to healthcare and how AI plays a role in it. This will not only show your genuine interest but also help you align your answers with their goals.
✨Showcase Your Hands-On Experience
Be ready to discuss your recent projects where you've built and shipped AI agents in production. Highlight specific challenges you faced and how you overcame them, especially in relation to clinical data and real-world applications. This will demonstrate your practical skills and readiness for the role.
✨Prepare for Technical Questions
Expect technical questions that assess your understanding of AI systems, data pipelines, and production reliability. Brush up on your knowledge of vector databases, retrieval pipelines, and LLM endpoints. Being able to articulate your thought process and design decisions will impress the interviewers.
✨Emphasise Collaboration Skills
Lucis values collaboration with medical teams, so be prepared to discuss how you've worked alongside non-technical stakeholders in the past. Share examples of how you earned their trust and translated complex requirements into actionable workflows. This will highlight your ability to bridge the gap between tech and healthcare.