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 vibrant team culture in Paris.
- Other info: Fast-paced environment with opportunities for rapid learning and growth.
- 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.
- Data pipelines — ingestion and normalisation from labs (Eurofins, Randox), wearables, and third-party partners.
- 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.
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 an intro call, technical interview, at-home case study, deep dive, and team chat.
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 in London employer: Lucis (YC P25)
At Lucis, we are dedicated to revolutionising healthcare by making preventive health the norm across Europe. Our vibrant Paris hub fosters a collaborative and innovative work culture where every team member is empowered to take radical ownership of their projects, ensuring rapid growth and impactful contributions. With a focus on employee development and a commitment to using cutting-edge AI technology, we offer a unique opportunity for passionate individuals to make a meaningful difference in human longevity.
StudySmarter Expert Advice🤫
We think this is how you could land AI engineer in London
✨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 AI projects, especially those that relate to 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 in Europe.
✨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 in London
Some tips for your application 🫡
Show Your Passion for Health:Let us know why you're excited about preventive health! Share any personal experiences or interests that connect you to our mission. We want to see your genuine enthusiasm for helping people live healthier lives.
Highlight Relevant Experience:Make sure to showcase your 8+ years of experience in building and shipping software and ML systems. We’re looking for hands-on examples of AI agents you've worked on, so don’t hold back on the details!
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to explain your skills and how they relate to the role. We appreciate a well-structured application that gets straight to the point.
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 preventive health. Familiarise yourself with their approach to healthcare and how AI plays a role in it. This will not only help you align your answers with their values but also show your genuine interest in their work.
✨Showcase Your Technical Skills
Be ready to discuss your experience with AI agents, data pipelines, and production reliability. Prepare specific examples of projects where you've built and shipped software or ML systems. Highlight your hands-on experience with vector databases and retrieval pipelines, as this is crucial for the role.
✨Prepare for Collaboration Questions
Since you'll be working closely with medical teams, think about how you've successfully collaborated with non-technical stakeholders in the past. Be prepared to share examples of how you translated complex requirements into actionable workflows, earning trust along the way.
✨Emphasise Your Passion for Health
Lucis is looking for someone who is genuinely obsessed with health. Share your personal experiences, whether it's tracking your own biomarkers or staying updated with clinical literature. This passion will resonate well with the team and demonstrate that you're a great cultural fit.