AI engineer in London

AI engineer in London

London Full-Time 80000 - 100000 £ / year (est.) Home office (partial)
LUCIS

At a Glance

  • Tasks: Build AI agents for preventive health, transforming clinical data into actionable insights.
  • Company: Lucis, a pioneering company focused on human longevity and preventive healthcare.
  • Benefits: Competitive salary, relocation support, and a collaborative work environment in Paris.
  • Other info: Fast-paced culture with opportunities for rapid growth and innovation.
  • 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.

At Lucis, we 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.

We're building AI agents that act as a doctor for preventive health — analyzing 110+ biomarkers, reasoning over clinical data, and delivering protocols that change how people age. The system works. 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 actually 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 behavior.
  • 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 normalization 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:

  • Python repo and TS monorepo (platform)
  • PostgreSQL + Prisma
  • AWS (Terraform)
  • GitHub Actions
  • Claude Code + Cursor
  • AI/agent framework: mostly Langchain ecosystem

The process:

  • 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 in London employer: LUCIS

At Lucis, we are dedicated to transforming healthcare into a preventive model, and as a Brand & Content Manager based in our vibrant Paris hub, you will play a pivotal role in shaping our voice and content strategy. We foster a collaborative work culture that values radical ownership and encourages innovation, providing ample opportunities for professional growth and the chance to work alongside passionate individuals committed to making a meaningful impact in health education. With access to cutting-edge AI tools and a supportive environment, Lucis is an exceptional employer for those looking to contribute to a forward-thinking mission in the heart of Europe.

LUCIS

Contact Details:

LUCIS Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI engineer in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like LUCIS!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI engineer at LUCIS.

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like LUCIS.

Apply Directly through Our Website

When you find a suitable opening like AI engineer at LUCIS, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI engineer in London

AI Agent Architecture
Multi-Agent System Design
Clinical Data Analysis
Data Retrieval Pipelines
Vector Infrastructure
Embedding Pipelines
RAG Architecture

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at LUCIS, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at LUCIS. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at LUCIS

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at LUCIS!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.