at Capgemini
ConsultanciesPosted 12 days ago
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**Forward Deployed AI Engineer:** Design, prototype, and iterate on Capgemini's AI-first operating system, automating offer creation. Collaborate with senior leaders, ensure technical rigor, and ship working capability quickly.Requires strong AI/ML background, swift iteration, and close collaboration. Key responsibilities include designing agent skills, evolving platform architecture, and serving as the technical reviewer.
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Full Job Description
Role Overview
Mission:
Build and improve the AI-first operating system Capgemini uses to create its Data & AI offerings, and make sure what it produces is technically sound before it reaches leadership.
Role:
You own the engineering edge of the offer factory. You design, prototype, and iterate on the agent skills and the operating system that automate offer creation, covering everything from gathering inputs, mining proven playbooks, and running vertical and analyst research, through to shaping the value proposition, big idea, and storyline. You do this in close collaboration with the VP of AI Engineering, evolving the platform's architecture, tooling, and skill library as you go.
This is fundamentally a co-creation role. You work side by side with the best engineering and sales leaders Capgemini has to shape what the company sells in Data and AI globally. The offer factory is where their expertise and your engineering come together, and you are the person who turns that shared thinking into working capability.
You are also the technical reviewer of what the AI produces. Before any research pack, positioning, or narrative goes to global offer owners such as the Head of AI Europe, Chief Portfolio Officer, and Chief AI Officer, you check that it is credible, feasible, and defensible. Your judgment is the quality gate that keeps the speed of automation from outrunning technical rigor.
Why it's a forward deployed engineer:
This is a hands-on, embedded role that sits between the platform and the people who sell. You ship working capability quickly, gather feedback straight from offer contributors and owners, and fold it back into the system. The impact is direct: you shape how Capgemini builds offers and what it takes to market.
Profile:
A strong engineering background in AI, ML, software, or data is essential. You need it to prototype and give useful feedback, but even more to judge whether AI-generated offer content holds up technically. You move fast, work iteratively, and collaborate closely with senior engineering and portfolio leadership.
