The FDE role is the most in-demand technical position of 2026 — and most enterprise engineering teams are not ready for it. This program changes that.
A Forward Deployed Engineer (FDE) is a technical engineer who works directly at or with a customer organisation to discover requirements, build AI solutions, deploy them into production, and drive adoption. The role combines deep engineering skills with customer empathy, problem decomposition, and delivery ownership.
Job postings for FDE roles have grown over 800% since 2025. OpenAI launched "The Deployment Company" in 2026 — a large-scale enterprise AI deployment initiative built entirely around forward deployed engineers embedded within customer organisations. Google, Adobe, Anthropic, and Palantir have all significantly expanded their FDE teams.
The demand is clear. The talent is not. Most engineers have deep technical skills but lack the discovery, deployment, and adoption skills the FDE role requires. That is the gap this program closes.
RAG architecture, agentic workflow design, production deployment, monitoring, eval pipelines, red-teaming, and AI observability — the engineering skills that turn a prototype into a deployed system.
Stakeholder discovery, requirements translation, client communication, adoption planning, and change management — the skills that turn a deployed system into one that people actually use.
This is an enterprise corporate training program — not an individual career course. It is designed for L&D and HR leaders at IT services firms, consulting companies, and large technology enterprises who need to build FDE capability across a team.
Software developers, AI engineers, solutions architects, and technical consultants who build AI systems but haven't yet developed the discovery and deployment skills to function as FDEs.
IT services and consulting firms deploying AI for clients. Large enterprises deploying AI internally across business units. Technology companies building AI-powered products for enterprise customers.
Engineers who can independently take an AI use case from discovery to deployment to adoption — without hand-holding at every stage.
3 days. Participants leave with a deployed working system, a client discovery framework, and a 90-day adoption plan — not a certificate of attendance.
Every module combines concept, live build, and real-world scenario. Participants work on a single end-to-end use case throughout — not isolated labs that don't connect.
MORNING
Stakeholder discovery frameworks · Translating business requirements into technical specs · Identifying the right AI use case (not just the most interesting one) · Discovery doc template
AFTERNOON
RAG architecture deep dive · Vector store selection and retrieval pipeline design · Hybrid retrieval with re-ranking and grounding · Hands-on build: working RAG system on client data
MORNING
Agentic workflow design · Tool orchestration and MCP integration · Human-in-the-loop patterns · Multi-agent coordination · Claude Code for rapid FDE delivery · Live build: agentic layer on Day 1 RAG system
AFTERNOON
Production deployment patterns · API design and streaming · Authentication and access control · OpenTelemetry instrumentation · RAGAS eval pipelines · Monitoring dashboards · Live deployment to cloud
MORNING
AI red-teaming fundamentals · OWASP LLM Top 10 · Prompt injection and data residency · Guardrails and NeMo implementation · Responsible AI audit framework · Red-team report template
AFTERNOON
Adoption planning frameworks · Change management for AI deployment · 90-day adoption plan · Stakeholder demo preparation · Capstone: full system demo + discovery doc + adoption plan — panel reviewed
What participants leave with: A deployed RAG and agentic system built on a real use case from their organisation · A client discovery framework and template · A red-team findings report · A 90-day adoption plan · The confidence to run the full FDE cycle independently.
A Forward Deployed Engineer is a technical engineer who works directly at or with a customer organisation to discover requirements, build AI solutions, deploy them into production, and drive adoption. The role combines deep engineering with customer empathy, problem decomposition, and delivery ownership. Job postings for FDE roles have grown over 800% since 2025.
L&D and HR leaders at IT services firms, consulting companies, and large technology enterprises who need to train their existing engineers — software developers, AI engineers, solutions architects — to function as FDEs for internal or client-facing AI deployments.
Participants should be comfortable with Python and have basic familiarity with APIs. Prior AI or ML experience is helpful but not required — the program builds from fundamentals to production in 3 days. We recommend the GenAI Developer Track as a prerequisite for teams with no prior AI exposure.
The discovery call includes a scoping session where we understand your technology stack, your industry, your target use cases, and your team's current capability level. All labs and the capstone project are designed around real scenarios from your business context — not generic examples.
Yes — remote delivery is available for international teams. The program has been designed to work in both in-person and virtual formats. Contact us for a discovery call to discuss the right format for your team.
Yes. The FDE Enterprise Program works well as a follow-on to the GenAI Developer Track or Agentic AI Bootcamp. We also design multi-program learning journeys for organisations that want to build capability across multiple levels — from AI for Leaders through to FDE-level engineering.