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APPLIED AI FELLOWSHIP · ADVANCED SPECIALIZATION

Forward Deployed AI specialization

Learn to work with a stakeholder, turn requirements into a working AI system, and demonstrate that it can be tested, deployed and handed over safely.

What does a forward deployed engineer do?

A forward deployed engineer works with the people who will use a system. They clarify the workflow and success criteria, build and integrate the solution, then validate how it performs with the people who will operate it.

Who is this specialization for?

It is an advanced path within the 12-week fellowship for experienced professionals who can demonstrate coding, API integration and debugging skills, or who are prepared to develop those skills through the engineering bridges. The core fellowship plans for 6–10 hours a week. Bridge work and additional practice can take longer.

What will I build?

Use one client-style project to connect discovery, architecture, AI-assisted implementation, integration, security, evaluation and deployment. For example, a service team might build a source-grounded assistant that drafts an account brief, checks permissions before a handoff, and records what happens when an integration fails.

  1. Discover and agree scope. Run a stakeholder discovery exercise. Capture requirements, a measured baseline, exclusions and acceptance criteria in milestones 1 and 11.
  2. Build and integrate. In milestones 2–8 and the implementation and integration bridges, justify the architecture and tool choices. Show your own code or configuration, how you verified AI-assisted changes, and observed permissions, retries and failures.
  3. Deploy, evaluate and hand over. In milestones 9–12 and the deployment bridge, deploy a bounded release in an authorized training environment. Show smoke checks, rollback, business impact and handover, then defend the project in a live review.

What evidence do reviewers inspect?

Implementation and debugging

  • Runnable implementation and own contribution
  • Input validation and error handling
  • Observed failure, diagnosis and correction

APIs, MCP and authorization

  • Actual contract and authorization enforced outside the model
  • Observed approved and denied actions
  • Idempotency and ambiguous-result recovery

Deployment and operations

  • Identified environment and version
  • Observed permission and failure checks
  • Logs, rollback and accountable handover

To demonstrate the specialization, complete all three human-reviewed bridges, pass the live capstone, and receive an end-to-end capability assessment. The result describes the scope and supervision needs demonstrated by your work. Vendor certification and employment are separate.