Founding Forward Deployed Engineer - AI

AI-native orchestration layer for industrial operations.

Using AI, they help operational teams collect, understand, and secure customer orders before they reach the ERP. And automate at scale their operations.

The long-term ambition is to become a true Operating System for industrial workflows.

They just closed a pre-seed round with top-tier VCs and are now entering a critical phase: structuring the go-to-market, accelerating traction, and iterating closely with their first customers.

You'll sit at the intersection of engineering, product, and customer strategy: building the integrations and workflows that make the product work in the customers’ environment, and carrying everything you learn in the field back into the core product.

This is a hybrid deployment engineer / deployment strategist role. You own the customer outcome end-to-end - from scoping the problem on-site, to shipping the integration, to making sure the value actually lands and renews. Your responsibilities look a lot like those of a hands-on startup CTO for each account you run: small team, high stakes, full ownership.

Because you're one of the first hires, you'll also define how this function works - the deployment playbook, the implementation standards, and the feedback loop between the field and the product team are yours to build.

On a typical day you might:

• Own deployment at the client – lead kickoff and discovery on-site, scope the solution against real workflows and data, plan the implementation, and drive the project from pilot to production against clear timelines and success criteria.
• Build the integrations that make it real – connect the platform to customer ERPs (SAP S/4HANA), EDI, SFTPs, APIs, and portals; write production code to handle their data, their edge cases, and their compliance constraints.
• Manage the customer relationship – be the trusted technical owner our customers rely on, run recurring business reviews and check-ins, handle escalations, and turn a successful pilot into an expanding, renewing account.
• Close the loop with product – translate what you see in the field into reusable features and product requirements, and contribute directly to the core platform when a customer need should become a product capability.
• Set customers up for success – design evals and guardrails for their use cases, train their teams, and manage change so adoption sticks after go-live.

• 4+ years shipping software in production, with real customer-facing time – you've owned software end-to-end inside a customer's environment: integration, rollout, debugging live issues, and keeping it running
• Turning ambiguity into a plan – you can walk into a vague business problem, run discovery with users and domain experts, and come out with a concrete technical scope, success criteria, and a path to production
• Enterprise integration in the real world – you've integrated into systems you don't control (ERPs, EDI, SFTP, third-party APIs) and handled the messy, undocumented, edge-case-ridden data that comes with them
• Making LLM systems production-trustworthy – you've built and deployed applications on top of models (Claude, GPT, or similar) and know how to get them to a specific customer's bar through evals, guardrails, and iteration (you build on models, you don't train them)
• Owning the technical relationship – you're the person in the room with the customer: leading workshops, translating between their ops teams and their IT, and presenting to leadership with equal ease
• Driving a deployment as a project – you scope, set expectations, sequence the work, and push an engagement from pilot to live on a timeline, with a named counterpart on the customer side
• Hands-on engineering as the floor – you ship production code in Typescript or Python against SQL/NoSQL databases; strong fundamentals are assumed, but you optimize for working systems in the field over elegance
• Top notch communication skills – you can discuss very technical topics with non-technical stakeholders
• Fluent in French and English

Technical Stack:

• Backend: A mix of Python and Typescript with PostgreSQL on the AI, harness & data side; Ruby/Rails on the platform side.
• AI/ML: AWS Bedrock, LangChain/LangGraph, vector databases, prompt engineering, evals
• Integrations: SAP S/4HANA, Infor SyteLine, EDI, SFTP, REST APIs, customer portals; structured, semi-structured & unstructured data (emails, PDFs, Excel)
• Infrastructure: AWS, Kubernetes, GitHub Actions
• Monitoring: Langfuse, Sentry, HyperDX
  

• Strong VC backing – Well-funded with runway to execute and scale
• Office in Paris, flexibility with remote, but team moments are important - ideally the candidate will be based in Paris.
• Salary up to 140 K€ depending on seniority + BSPCE