A Deloitte Microsoft AI and Data Forward Deployed Engineer sits in the middle of three things that usually move at different speeds. There is the client and their business problem, the engineering work needed to build something real, and the enterprise guardrails like security, risk, and reliability. The role exists because GenAI projects fail when any one of those is treated as an afterthought.
In this course, we will prepare for that exact job shape. We will practice how to take a fuzzy request like “build us a copilot” and turn it into a clear use case, a build plan, an Azure architecture, and working code that can survive real client constraints. Let’s first map what the role actually does in an engagement.
Forward Deployed Engineer (FDE) means an engineer who is embedded with clients and responsible for getting working software into their hands fast, not just writing internal code. In the Deloitte Microsoft AI and Data version of the role, that includes rapid prototyping of GenAI solutions side by side with senior client stakeholders and engineers, then pushing toward delivery that shows measurable business impact.
A common way Deloitte staffs this is with a small delivery group. A pod is a small team, often a few engineers, that owns delivery end to end for a slice of the client problem. In that pod, the FDE contributes independently, runs working sessions, and helps translate what the client cares about into software that actually works in the client environment.
Consider this situation. A client wants a GenAI assistant for internal policy questions, and they want it quickly, but they also need it to respect access controls and be supportable after launch. As the FDE, you are expected to move with speed and precision while still making architecture choices that balance quality, safety, latency, cost, and model risk.
That mix of building and decision-making is why interview prep cannot be only “can you code” or only “can you talk to clients.” The interview needs signals that you can build production-quality code with testing, CI/CD, logging, versioning, and documentation, and that you can work directly with client leaders and technical teams in fast-moving, ambiguous delivery. Next, we separate what is explicitly stated in the job posting from what is likely to show up in interviews.