Become a Forward Deployed Engineer in 6 months
Build production AI, embed with the customer, own the outcome. Learn to turn a messy business problem into a deployed AI system — the hottest hybrid role in tech.
We teach mindset, not memorization
- Duration6 months (24 weeks) of live instructor-led sessions
- Commitment2 live sessions/week (Sat + Sun) + 6–8 hrs self-paced
- ModeOnline · Live + self-paced · Recorded sessions
- Ideal forSoftware engineers, SDETs, data/ML engineers, solutions & support engineers with basic Python
- Next cohortNov 16, 2026
Forward Deployed Engineer: the fastest-growing role in AI
FDEs embed with customers, understand the real problem, and ship AI inside real constraints. The market is paying a premium for the ones who can do both halves.
The role at the intersection of three disciplines
An FDE does two jobs at once: the consultant's job of finding the real problem, and the engineer's job of building and running the system that solves it.
Six moves from business reality to shipped AI
Shadow the customer, see the real workflow, map stakeholders and constraints.
Separate the loud problem from the real one. Write a testable use case.
Choose the architecture: LLM + RAG, agents, classical ML, or no AI at all.
Latency, cost, privacy, legacy systems — ship inside the box the business lives in.
CI/CD, observability, guardrails, rollback plan — your code runs where it matters.
Measure impact, iterate with the user, hand off a healthy system — not a demo.
What you'll master
Module-level detail across the full program.
- The FDE Role & Mindset — FDE vs SWE vs Solutions vs Product Engineer, the Palantir model, FDE market & hiring landscape, day-in-the-life
- Engineering Foundations — Python for production, Git & workflows, REST APIs with FastAPI, SQL, Docker basics, AI-assisted coding
- Consulting track — understanding the business problem, asking better questions, framing a testable AI use case
- You produce: your first working AI tool + a clear problem statement
- LLM Applications — fundamentals, prompting patterns (CoT, ReAct), structured outputs, function/tool calling, model selection & cost
- Context Engineering & RAG — embeddings, semantic search, vector DBs (pgvector, Qdrant, Pinecone), chunking, hybrid retrieval, re-ranking, grounding
- Agentic AI — agent design patterns, LangGraph, CrewAI, MCP tools, multi-agent workflows, human-in-the-loop
- Evaluation & Reliability — golden datasets, LLM-as-judge, DeepEval, handling non-determinism, accuracy matrices, regression testing for AI
- Consulting track — requirement discovery, stakeholder mapping, PRDs & solution design docs, communicating trade-offs
- You produce: a deployable AI system + architecture diagram + design-decision log
- Enterprise Integration — connecting AI to CRM/ERP (Salesforce, SAP), ticketing (Jira), Slack, SQL/legacy systems, webhooks, event-driven services
- Production Deployment & LLMOps — CI/CD, cloud deployment (AWS / Azure / GCP), observability (LangSmith, Langfuse), latency & cost optimisation
- AI Security, Guardrails & Governance — prompt injection, PII detection, guardrails (NeMo Guardrails / Guardrails AI), red-teaming, audit trails, compliance
- Consulting track — ROI case (revenue · risk · cost), delivery planning, scope management, demo delivery & executive storytelling
- You produce: a production-grade system + deployment docs + red-team report
- Capstone Client Engagement — a simulated end-to-end customer engagement from first discovery call to production handoff
- FDE Interview Preparation — problem-decomposition cases, AI system design rounds, customer role-play, take-home builds, portfolio walkthroughs
- Capstone deliverables — discovery doc · solution architecture · deployed AI service · evaluation dashboard · red-team report · 90-day adoption plan
- Demoed live to a mentor panel
You build systems like these
Each project maps to a pattern enterprises are hiring FDEs to deliver.
Multi-language triage + RAG over help docs — route tickets by intent, priority, language.
Q&A over internal docs with inline citations and permission-aware retrieval.
Auto-generate test suites from API specs. Detect breaking contract changes before release.
Match records across statements, flag exceptions, and generate human-reviewable summaries.
Pull company data from web + sales calls into the CRM — scored, deduped, source-linked.
Guardrailed LLM gateway with PII redaction, prompt-injection filter, and audit logs.
The modern applied-AI stack
Roles you can target
Outcomes data coming with our first FDE cohort.
Learn from senior engineers who have deployed AI systems inside banks, SaaS companies and global product teams. The curriculum is co-designed with practising FDEs and applied-AI leads.
Where our graduates work
Real students. Real offers.
"DigieKnowledge gave me structured, high-quality learning experiences that went beyond theory. The Academic and Job courses bridged the gap between industry practices and academic depth and eventually helped in landing a job."
"DigieKnowledge helped me strengthen both my technical expertise and leadership skills. The mix of hands-on learning and real-world case studies gave me practical strategies I could apply directly in my projects."
"As a Quality Engineer, DigieKnowledge helped me sharpen both my technical and analytical skills. The courses on test strategy, automation, and defect analysis were highly practical and industry-focused."
Pricing is tailored to your background and payment plan. Book a 15-minute discovery call and we'll share a written quote within one business day.
- Flexible EMI / instalment options
- Employer sponsorship & GST invoice available
- Refund policy: full refund within 7 days of enrolment if unsatisfied
Common questions
Everything you might want to ask before joining.
Basic Python is enough. Phase 1 covers foundations and Phase 2 builds AI depth from scratch — LLMs, RAG, agents, evaluation.
Yes. Evaluation and testing of AI systems is a core FDE skill, and SDETs already think in test cases and reliability — Module 6 is a natural extension.
Every phase ends with something you build and deploy. The capstone is a live-demoed, end-to-end client engagement reviewed by a mentor panel.
Yes — the same career support as every program, plus a dedicated FDE interview-prep module (problem-decomposition cases, AI system design, customer role-play).
Yes. Recordings stay in your dashboard for the full program duration plus 3 months after completion.
Drop your details and we'll get back within one business day.