Fullstack Software Engineer - Mo team (AI Health Companion)

Location

Paris, France

Employment Type

Full time

Location Type

Hybrid

Department

Engineering

About the Company

Alan is building a vertically integrated health partner that unites insurance and smart healthcare delivery into one seamless system. Our vision is to make prevention the new norm of care for all. We partner with tens of thousands of companies across France, Spain, Belgium, and Canada, serving over a million members.

Core Mission

Help people live in good health to 100% while helping employers feel proud, turning health benefits from a cost centre into their most valuable investment. By connecting all aspects of care we create the most member‑centric experience, reducing claims costs while generating new monetization opportunities.

Our Work Environment

• Mission is the Boss — we think long‑term and are methodical optimists who take risks, seeking our mission’s success above all else.
• Distributed Ownership — everyone owns their decisions and results.
• Radical Transparency — all information is accessible and written‑first, so everyone can make the best decisions asynchronously.
• Always Growing — direct, positive, and caring feedback, combined with self‑growth ownership.

Product Overview

We’re building Mo — a health companion for everyone, an intelligent, empathetic, multimodal LLM‑based conversational AI assistant able to prescribe, triage, and proactively follow up on care. Mo will provide instant, 24/7 access to personalised medical expertise through chat, voice, or video.

Key Responsibilities

• Deliver the most memorable chatting experience, creating a world‑class snappy and delightful interface.
• Scale our systems to serve 100x more users, preparing Mo for a few million members, focusing on latency, error rate, and error recovery.
• Integrate Mo with all Alan services (digital chat, physical location mapping, tailored prevention programs) to increase the value delivered to members.
• Extend our architecture to support future needs of Mo, such as more context, new skills, and broader country reach.

Who We’re Looking For

We are seeking Product Engineers with 5+ years of experience who are excited about building state‑of‑the‑art AI systems and applying them to real‑world, high‑stakes problems in healthcare.

• Work at the frontier of LLMs, multi‑agent architectures, and human‑in‑the‑loop learning, with production deployment of solutions that help real people.
• Implement new capabilities for Mo across engineering, data, and medical expertise.
• Scale systems from thousands to millions of active members rapidly.
• Influence system architecture and code quality.
• Mentor engineers and contribute to product and engineering culture, including hiring and interview design.

Nice to Have

• Strong background in software engineering and systems architecture, with a focus on back‑end engineering.
• Experience with traditional ML, LLMs, or ML dev‑ops.
• Product‑mindful mentality, aiming for impactful solutions.
• Self‑directed, pragmatic, humble, collaborative, and enthusiastic about learning and teaching.
• Fluent in English (French not required).

Benefits

• Fair rewards – generous equity packages complement the base salary.
• Flexible office – HQ space, sponsored co‑working hubs, or full‑remote experience with equipment sponsorship.
• All the tools you need – high‑quality equipment such as Macbook Pro, keyboard, laptop stand, monitor, noise‑canceling headphones.
• Flexible vacation policy and flexible working hours.
• Delightful healthcare insurance – 100% coverage for you and your children, 90‑100% for partners (permanent contracts only).
• Transport benefits – country‑specific commuter benefits.
• Learning and training opportunities – free books and budget for conferences.
• Personal growth through coaching – paired with a dedicated coach from day one.
• Parental leave – extended leave for new parents.

Equal Employment Opportunity

We strive to build a diverse workforce and encourage candidates from all backgrounds, especially underrepresented groups, to apply. We focus on potential and curiosity above strict checklists.