Level

Alan

Fullstack Software Engineer (x/f/m) - Agentic Platform

Alan is hiring a Fullstack Software Engineer (x/f/m) - Agentic Platform for a remote role open to applicants in France. Level rates it ; you can apply on Alan.

Level's read on this job

  • Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include Python, FastAPI and Sqlalchemy.
  • Level lists 129 other open roles at Alan.
  • The role was posted in the last few days.

AI in this role

Build and scale agentic AI platforms and fullstack services for a health insurance prevention app using modern Python and LLM technologies.

pythonfastapisqlalchemypydanticaitemporalpostgresqlmcpdaytonaterraformawsreactvite+1
ai-agentsml-opsfullstack-engineeringagentic-platformsllm-integrationdistributed-systems

Health can’t wait.

Not for symptoms to get worse. Not for a six‑month appointment. Not for a system to catch up. But that’s exactly how healthcare works today. You wait, until you can’t.

Alan exists to end the wait.

Health is a universal right, and we believe this right can only become real when it’s coupled with prevention. We need to stop treating health as something we repair and start treating it as something we build, every day. It’s not solely a question of willpower. It’s the healthcare system itself that needs to work for everyone, in a sustainable way.

So we are building the new standard in prevention insurance. Alan is the first company that integrates insurance, prevention, and care into a single, acclaimed user experience.

We are on an incredible journey to build a global leading company, with a unique culture. We already partner with 40K+ companies of all sizes, serving more than 1M+ members, and have reached €800M+ in ARR.

Prevention as the new norm. That's what we're building with our team of 1000+ people. If it speaks to you: we're hiring across France, Spain, Belgium, and Canada. And beyond.

⭐ The Engineering team ⭐

In our engineering team, we build the infrastructure, interfaces, and applications to provide first-class service to our members, health professionals, and even ourselves!

Being an engineer at Alan means joining a team of talented, committed and passionate engineers, with a lot of product interaction.

We move fast, with a lot of ownership, and are proud to tackle big problems!

Our process is very simple: those who make product decisions are the same ones who build them.

Want to know more? Read this article if you want to discover how life as an Engineer at Alan and this article on our Engineering career pat

🛠️ The stack

Python services on FastAPI, async SQLAlchemy and PydanticAI, Temporal for durable execution, PostgreSQL, MCP, Daytona sandboxes, various LLM model providers, Terraform on AWS, React with Vite. Our main backend is a Flask monolith. We deploy daily and believe in distributed ownership: you build it, you own it.

🤖 The Agentic Platform area

In 2027, we expect to run more AI agents than we have employees.

Agents already do real work at Alan. They answer members' health questions, resolve support requests, read medical documents, detect fraud, automate operational tasks, and write a large share of our code.

But every team building an agent ends up solving the same hard problems again: how to call models safely with health data, how to give an agent tools and the right permissions, how to know whether a prompt change made it better or worse, how to debug what it did. The result: several agent frameworks and evaluation stacks, each with its own security and compliance story.

The Agentic Platform area was created to fix that. Our mission: make it cheap, fast and safe for every Alaner or crew to build, run and improve agentic products and workflows.

We own the environment agents run in (infrastructure, runtime, evaluation, observability, skills lifecycle), with security, privacy and compliance by design, and the generalist products on top: Hopper and the Agent Studio. Product teams and all Alaners own their agents, skills, and their outcomes. We give them the paved road.

Two crews, one team:

  • Hopper is every Alaner's AI companion. Five months after it started, 80% of Alaners use it, 3k sessions are created each day, and about 30% of our pull requests are opened from it (watch how we built it).

  • AI Product Platform builds the shared blocks every AI product at Alan runs on. For instance, our ops teams now build agents autonomously on our Ops AI Platform (read how, watch the talk).

🧩 Problems you'll only find here

Run agents at scale

  • 🧠 One runtime for every AI product. A shared agent framework, from a single model call to multi-agent workflows with live streaming, and one gateway to every model: routing, failover across providers, quotas and cost per use case built in.

  • ⏳ Agent sessions that last for hours. Durable sessions, started from the web, Slack, Linear or GitHub, that survive pod restarts and deploys, and pick up exactly where they left off.

  • 📦 Sandboxes at scale. An isolated environment for every agent session and every evaluation, on an infrastructure compliant with sensitive data, with negligible boot overhead.

Make agents trustworthy and proactive

  • 🔌 One tool gateway to the whole company. An MCP gateway that connects agents to internal tools and data, external services, computer use, managing identity and credentials.

  • 🔐 Agents safely acting on critical data. We give each agent no more than the access it needs. Every tool call goes through identity, permissions, confirmations and audit. No sensitive data leaks.

  • 🧪 Evals you can replay in time. Re-run an agent or skill against production as it was at a past point in time, on real data, safely isolated. Anyone can ship knowing their change is an improvement rather than a regression.

  • 🔁 Agents and skills that proactively fix themselves. Every run is traced, and every human correction, failed tool call or escalation becomes a prioritized fix that Hopper can apply.

Put agents in everyone's hands

  • 📚 Skills as a product. A registry where Alaners and teams publish, share and version their skills, so that nothing needs to be repeated twice.

  • ✨ AI that non-engineers can own. Alaners who ship code through Hopper, Operators or Sales who build their own agents or skills in our Studio and operate them from their day-to-day tools.

  • ⏰ Automations and artifacts. Agents that run on a schedule or on an event, and build the dashboards and hosted sites that become the go-to places for collaboration.

⭐ Is it you we’re looking for?

What you'll do

  • Own some of the problems above end to end, from design to production, with significant influence on architecture and code quality

  • Work closely with the people who use what you build: Alaners, product teams, ops

  • Own reliability, cost and security in production

  • Mentor engineers, contribute to our product and engineering culture, and help build the team

Experience we value

  • 3+ years in software engineering, with solid backend fundamentals

  • Platform-leaning or product-leaning: both are welcome. Depth in at least one of: distributed systems and runtimes, evaluation and data quality, security and authorization, product UX

  • A good sense of user and developer experience, whatever you build

  • You built products, platforms or infrastructure used by other people

  • Experience with LLM APIs, agent frameworks, evals or MCP is a strong plus; ML or MLOps experience is a plus

Mindset we value

  • You measure success by adoption, not by what is available

  • You make concrete tradeoffs between speed, reliability, cost, security and user experience

  • You simplify complexity with clear abstractions and maintainable code

  • You care about whether people can understand and verify what an AI system did

  • You keep up with the latest AI technology and know the open-source AI ecosystem

  • Self-directed, pragmatic, humble, collaborative, enthusiastic about learning and teaching

  • Excited about AI changing who can build, investigate and automate work

Above all, we look for high potential and curiosity: make sure to show us this when you apply. Everything else is a bonus.

You should be fluent in English (no French required).

🌍 How we work
  • Location: you must be legally eligible to work in France, Belgium, or Spain.

  • Remote work: we offer remote work flexibility, but we value in-person collaboration.

🙌 Perks & Benefits

At Alan, we believe that being in good health is a basic need, and it starts with our employees. This is why Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers.

Therefore, we offer:

  • Fair rewards. Generous equity packages complement your base salary.

  • Flexible Office. Amazing office space at our HQ, sponsored co-working hubs or a full-remote experience with home office equipment sponsorship, we want you to live where you’re the happiest.

  • All the tools you need. Top of the range equipment: Macbook Pro, keyboard, laptop stand, monitor, and noise-canceling headphones.

  • Flexible vacation policy and flexible working hours. Organize your time as you wish.

  • Delightful healthcare insurance: Extremely comprehensive health insurance - 100% for you and your children, 90-100% for partners depending on your country (permanent contracts only).

  • Transport. Country-specific commuter benefits.

  • Learning & Training opportunities. A highly flexible Training policy free books and budget to attend and speak at conferences if the opportunity arises.

  • Personal growth through coaching: At Alan, coaching isn't just a perk - it's core to who we are. Every Alaner is paired with a dedicated coach from day one, who helps maximize their impact, nurture engagement, and navigate Alan's values to develop their full potential. Learn more about our coaching culture.

  • Parental leave. Extended parental leave for all new parents.

 

Important note: we hire people, not roles.

If you're excited about this opportunity but don't check every box, we'd love to hear from you. Everyone, no matter how underrepresented, should feel free to apply as it can only bring learnings or success.

If you identify yourself as a woman: Did you know that research shows women often apply only when meeting 100% of requirements?

Remember, this is just a guide, not a checklist.

We'll be thrilled to receive your application!

🔖 Check out our About Alan and Career pages, as well as our Medium, blog and Glassdoor page for more info.

🔄 A quick note about the process
Note: While you're applying for a specific area, you may join a different engineering team based on where we think you'll have the most impact. Check out descriptions of other areas here.

How we rate this

Fullstack Software Engineer (x/f/m) - Agentic Platform at Alan rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsML OpsFullstack EngineeringAgentic PlatformsLLM IntegrationDistributed SystemsPythonFastAPI

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Tell me about a project where fullstack engineering was part of your work. What did you do?
  4. Tell me about a project where agentic platforms was part of your work. What did you do?
  5. How have you integrated a large language model into a production application?

Adapt your resume

  • List these exact terms on your resume: AI agents, ML Ops, Fullstack Engineering, Agentic Platforms, and LLM Integration. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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