Forward Deployed Engineer

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Job Description Role summary

Our FDEs are deployed alongside the client's business and technology teams, they discover and frame the real problem, define the working solution, and stay accountable throughout build and value realisation.

An FDE independently owns a customer use case from discovery through production deployment and handoff and coordinates the contributions of the delivery team. The FDE partners with customer stakeholders, product teams, and engineering teams to define the problem, design the solution, build production-quality software, and drive measurable adoption.

The FDE combines strong technical execution with business and domain understanding. The client comes to them for both engineering judgement and business-value insight, and they shape, build, and industrialise solutions that deliver measurable outcomes.

The FDEs work with our wider business and technology teams and capabilities to- architect, design and deliver solutions that realise measurable outcomes for our clients.

The career path for our FDEs is to become a Principal ODE and ultimately be a recognised industry leader and become a VP Distinguished Engineer or VP Business Partner.

Discover and frame
• Lead discovery and problem framing with client stakeholders; separate the real problem from the stated ask.
• Define the success measures, value hypothesis, and target outcomes before anything is built.
• Shape the solution direction and make the key decisions that follow: capability changes, workflow redesign, platform choices, architecture direction, and where AI belongs in the operating model.

Solution and build
• Own the solution architecture and build the critical path hands-on; set the engineering, business, and delivery standard for the workstream.
• Deliver rapid prototypes, proofs of value, and production-ready increments that prove value early and de-risk decisions.
• Steer AI tooling and teams to produce production-quality output, and verify it before it ships.
• Verify generated output against both engineering and business failure classes, including reliability, security, performance, compliance, regulatory requirements, operational feasibility, and business outcomes.
• Bring applied AI and generative AI to the solution as a usable product, not a demo, designing and implementing AI-powered workflows with appropriate human oversight.
• Own the specification and acceptance criteria the pod and its tooling build against and sign off that what shipped is what was specified.
• Drive production readiness- reliability, security, compliance, observability, supportability, and operational sustainability- designed in from the start.
• Design solutions that balance technical excellence, business value, user adoption, and regulatory obligations.
• Bring expertise in one or more areas such as AI and agentic systems, software engineering, data and platform engineering, business architecture, operating-model transformation, workflow redesign, or digital product delivery.

Industrialise and hand off
• Turn prototypes into repeatable, reusable assets, playbooks, patterns, and accelerators, and hand off cleanly to delivery or managed services.
• Share client learning across the wider FDE capability.
• Ensure solutions are documented, supportable, measurable, and ready to scale beyond the initial deployment.

Enable and own
• Own the outcome…