Scenario
All open roles
Nº 08/Engineering

Full-stack Engineer

Team
Engineering
Location
Lyon or Paris
Type
Full-time
Reports to
Frontend Lead
Working language
English; French

A seasoned frontend engineer with an explicit mandate to propose and ship changes across the whole stack: the web app and its agent, the cloud API, the SDKs and the MCP server. Your center of gravity is the frontend, the agent chat, workflow editor, model and inference surface, billing, analytics and canvas, but boundaries are guidelines, not walls. You are AI-native and hands-on with modern AI SDKs. This role exists in 2026 because AI tooling collapses the cost of crossing those boundaries.

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01 Mission

  • Ship features across the web app — agent chat, workflow editor, model & inference surface, billing and seat management, analytics and Canvas.
  • Own the AI-surface experience: streaming responses, tool-call rendering, structured output, latency budgets and graceful error recovery on long agent runs.
  • Improve the AI layer and the agent surface end to end — tool calls, multi-step agents, structured outputs, model routing, compaction, transcript persistence, MCP integrations and prompt caching.
  • Keep the frontend healthy: patch security vulnerabilities (Dependabot, GitHub advisories, SOC 2 findings) on a steady cadence, and co-own the architecture choices that keep the app fast and coherent as it grows.
  • Open pull requests in the cloud API, the TypeScript SDK and the MCP server whenever the right fix lives there, and coordinate cross-stack PR trains with the backend and ML teams.
  • Bring AI pair-programming into the team's daily flow: the prompts, agents and Claude-Code-driven workflows that make everyone faster.

02 Scope of ownership

Owns
  • The frontend, end to end and all its features.
  • AI infrastructure and power-user tooling: the AI layer and the agent surface.
  • Full-stack reach: cloud API PRs, SDK and MCP-server extensions, cross-stack coordination.
Does not own
  • Cloud API architecture decisions.
  • The machine-learning inference layer and model-training pipeline.
  • Product roadmap and prioritization.
  • Support tickets and the QA process.

03 What we look for

  • Four to seven years in frontend or full-stack, ideally on a SaaS product with a non-trivial real-time or streaming surface.
  • Strong TypeScript and React or Next.js, comfortable reading Node/serverless code and confident enough to ship a Vercel Function, a SDK change or even an AWS Lambda.
  • Hands-on with at least one AI SDK in production — Vercel AI SDK preferred, Anthropic or OpenAI acceptable; you've shipped streaming chat, tool calls or structured output, not just demos.
  • A daily user of AI coding assistants (Claude Code, Cursor, Copilot) with a strong bias for action across the stack, and clear written English when proposing changes that touch other teams’ code.
  • Background in generative AI / image-video models.

04 Disqualifiers

  • A frontend-only mindset that refuses to open a pull request in the API or an SDK when the bug lives there.
  • No hands-on AI SDK experience: hasn't shipped streaming chat, tool calls or structured-output features in production.
  • Not a daily user of AI coding assistants; thinks in tickets rather than agents and prompts.
  • Treats dependency hygiene and security patching as someone else's problem.

05 How we hire2-3 weeks

  1. 01
    Intro call
    30 min
  2. 02
    Product session
    60 min
  3. 03
    Build live
    60-90 min
  4. 04
    Written POV
    Async, 48h
  5. 05
    References
    Parallel
  6. 06
    Founder conversation
    45 min