Forward Deployed Engineer

Quick answer: what is this job?

PALO IT is hiring a Senior Forward Deployed Engineer in Paris, Île-de-France, on a permanent contract (CDI) with a hybrid work model. You will embed with enterprise clients to take AI-powered products from discovery to pilot, production and adoption, using PALO IT's AI-first Gen-e²™ methodology. A client-facing consulting posture and 5+ years of hands-on engineering are required.

Who We Are

Building the AI-first frontier enterprise.

We are a global technology consultancy with a trademarked, AI-first approach—Gen-e2™. It redefines how enterprises build digital products and transform their organizations with AI. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

• We are small enough to care locally, big enough to deliver globally (10 countries, 450+ experts from 50+ nationalities)
• We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.
• We are robust and resilient (100% independent, 0 debt, founded 2009)
• We are AI-native professionals who invest in what we believe and work as a collective intelligence
• We are positive, courageous and deliver at the leading edge

What does a Senior Forward Deployed Engineer do at PALO IT?

As a Senior Forward Deployed Engineer at PALO IT in Paris, you embed with client engineering, product and domain teams at large enterprises, and own the journey from discovery and scoping to pilot, production and adoption. Think deploying an agentic AI workflow inside a health insurer, standing up an AI-powered platform for a bank, or designing intelligent automation for an energy leader. This is not staff augmentation: you build like a product engineer and own whether what you ship gets adopted and creates value.

Client delivery

• Deliver defined workstreams independently, from prototype through to production
• Frame ambiguous business problems in discovery and scoping sessions, asking the clarifying questions that shape the solution
• Build full-stack, AI-powered systems that deliver measurable client impact
• Surface risks and dependencies before they become blockers, and pick up unassigned work to drive it forward

Consulting & client engagement

• Build trust with technical and non-technical stakeholders, and present your thinking to senior decision-makers
• Propose how AI can improve the client's product beyond what was asked
• Bring field feedback back to the team to sharpen how PALO IT delivers

AI-native practice with Gen-e²™

• Work AI-first by default: GitHub Copilot, Claude Code, Cursor or Codex generate most of your requirements, code and architecture diagrams
• Apply prompt and context engineering, and critically review every AI-generated output, AI generates; engineers own
• Scout emerging GenAI tools and turn them into practical improvements for the team

What makes this role different at PALO IT?

With Gen-e²™, PALO IT generates 95% of a product, code, documentation, infrastructure as code and design with AI coding agents and its own tooling, and delivers end-to-end products 2–3× faster than traditional approaches. You will work hands-on with the latest AI tooling from Microsoft, GitHub, Anthropic and other global technology leaders, and help define what AI-native delivery looks like inside the enterprises PALO IT transforms. If ambiguity energises you more than a well-defined backlog, you'll thrive here.

What experience do you need for this role?

Must-haves

• A client-facing, consulting posture, non-negotiable. You are at ease running discovery sessions, presenting to senior stakeholders and working in the open
• Significant experience of hands‑on software development, ideally including cross‑functional or client‑facing work
• Proven ability to deliver a workstream independently in a fast-moving or ambiguous environment
• Solid full-stack, generalist foundations, ideally Java or .net on the backend and React or Angular on the frontend with strong system design and programming principles
• Experience building with LLMs or generative models, professionally or through substantial personal projects
• Clear communication with technical and non‑technical audiences, and the ownership to drive outcomes rather than wait for instructions

AI-native skills (required)

• Daily, hands‑on use of AI tools across your engineering workflow, you can show how AI is part of your working method, not just describe it
• A working grasp of prompt and context engineering, and t