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Founding AI Engineer @Plato (backed by Hexa)Hexa · Paris
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Founding AI Engineer @Plato (backed by Hexa)

🗓️ Posted 2026-09-07 Paris Fulltime Hybrid ICT
💰 Salary Not shared 📊 Market 6,667 EUR–9,583 EUR/mo

About the Company

als to work 5x faster, by putting their whole firm on autopilot. Plato already supports more than 30 law firms and 1 major insurance company's legal team, who use our solution daily to manage hundreds of active cases. Founded in January 2026 by Ben https://www.linkedin.com/in/ben-lasseri/ (CEO) and Alexandre https://www.linkedin.com/in/alexandredeboutray/ (CTO), we are backed by Hexa (formerly eFounders), Europe's leading startup studio. Hexa has launched over 35 companies, including unicorns such as Front, Aircall, and Spendesk, collectively generating more than 230M in ARR and raising over 750M in funding. Plato is live with real users, real data and real revenue, solving concrete legal workflows in production. We're now looking for a Founding AI Engineer to help us turn the latest advances in AI into reliable products used every day by legal professionals. YOUR MISSION You'll work directly with Alexandre https://www.linkedin.com/in/alexandredeboutray/ locale frFR , our CTO, at the intersection of AI, software engineering and product. Your job is not to do AI research for the sake of research. You'll experiment with models and approaches, understand what works, and turn the best solutions into reliable production systems. You'll work on problems such as building agentic workflows, making sense complex legal documents, designing autonomous long-running agents, and improving the quality and reliability of AI-generated outputs.

Responsibilities

  • ● Build AI-powered product features
  • ● Design and ship AI features used directly by lawyers
  • ● Be at the bleeing edge of the agentic stack: memory, sandboxes, code mode, lots of tools, subagents
  • ● Turn prototypes and experiments into production-ready feature
  • ● Work with complex data
  • ● Extract, structure and reason over large volumes of unstructured legal documents
  • ● Build robust data and document-processing pipelines
  • ● Experiment with different models and approaches to improve accuracy and reliability
  • ● Make AI work in production
  • ● Evaluate and improve agent outcomes through testing, evals and iteration
  • ● Optimize systems for quality, latency and cost
  • ● Build the backend services and infrastructure needed to run AI reliably at scale
  • ● Shape the product
  • ● Work directly with the founders and users to understand real-world problems
  • ● Move quickly from problem experiment production (think days, not weeks)
  • ● Take ownership of your projects from exploration to deployment
  • ● THIS ROLE IS FOR YOU IF
  • ● You like working close to founders and users, making pragmatic technical decisions, and shipping software that actually runs in production.
  • ● You'll thrive in this role if you: