Forward Deployed Engineer

Our client is a global professional services and technology consultancy. Our client is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services.

With our thought leadership and culture of innovation, we apply industry expertise, diverse skill sets and next-generation technology to each business challenge. We believe in inclusion and diversity and supporting the whole person.

Our core values comprise of Stewardship, Best People, Client Value Creation, One Global Network, Respect for the Individual and Integrity. Year after year, our client is recognized worldwide not just for business performance but for inclusion and diversity too. "Across the globe, one thing is universally true of the people of our client: We care deeply about what we do and the impact we have with our clients and with the communities in which we work and live.

It is personal to all of us." – Julie Sweet, our CEO This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments.

You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes. The market is beginning to understand what leading technology companies have demonstrated: AI products fail not because the models are weak but because deployment is broken.

The gap between a successful AI pilot and an AI capability that scales is bridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role.

Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.

Key Responsibilities Embed directly with client engineering and business teams to deploy, scale, and operationalize AI platforms — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — inside enterprise environments Own production outcomes end-to-end: time-to-value, reliability, adoption velocity, and scalability, with business metrics attached — not just delivery milestones Move from ambiguous business problem to working production system through rapid experimentation: days to prototype, weeks to production-ready Design and govern AI architectures across the full enterprise stack: i...

Report this job