Forward Deployed Engineer (AI)
capability building,
designed for your organisation.
A custom-built corporate programme for Senior developers, tech leads, and solution engineers (5+ years) deployed into client accounts to scope, build, and own AI solutions end-to-end. We design the curriculum around your tech stack, project archetypes, and target business outcomes — delivered by domain-expert trainers and reinforced through AI-evaluated assessments.
A modular syllabus, built to be tailored.
Below is our reference curriculum. Every syllabus we deliver is tailored to your customer-specific requirements module depth, sequencing, lab environments, and capstone projects are adapted to your team's starting point, tech stack, and target outcomes.
- What an FDE actually does: discovery to adoption ownership across the full lifecycle
- Case study: teardown of 3 real FDE engagements wins and failures across BFSI, retail, and manufacturing
- The 2026 AI solution landscape: where RAG dominates, where agents earn their keep, where classical ML still wins
- Lab: map your own client portfolio to FDE engagement archetypes
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Enterprise learning solutions built for corporate teams.
Go beyond standard classroom delivery with enterprise-ready learning infrastructure, managed execution, capability insights, and production-like practice environments designed for corporate scale.
Enterprise Command Center (LMS+)
Managed Batches (End-to-End Execution)
Capability Audits (Pre-Training Intel)
Custom Chaos Sandboxes
Demonstrable skills your team will apply on live projects.
Run a discovery conversation that produces a fundable solution sketch
Workshop facilitation, problem framing, JTBD mapping, AI-pattern selection, architecture diagramming within 5 days of first client contact.
Build production-grade RAG and agentic services on customer cloud
Chunking strategy selection, vector store choice, hybrid retrieval, re-ranking, multi-agent orchestration via LangGraph/CrewAI/AutoGen on Azure or AWS.
Operationalise AI services with observability, guardrails, and cost controls
OpenTelemetry traces, online evaluation, NeMo/Guardrails AI, semantic caching, model routing, fine-tuning when warranted.
Pass the joint NovelVista + client capstone panel
Each FDE delivers: discovery doc, solution architecture, deployed service, monitoring dashboard, red-team report, and 90-day adoption plan.
Earn the FDE certification credential
Cohort first-attempt completion rate of 89% across enterprise deployments. Two attempts permitted. Co-branded certificates available for ATP partner clients.
Become the AI champion in your client accounts
FDE alumni typically take a 2-3 grade leap in client-facing scope within 6 months and become the lead solution voice on AI deals.
Where your team is now vs where they'll be after the programme.
Where most teams start
- ·Senior developer or tech lead, but new to the FDE seat unsure how to scope an AI engagement from a discovery conversation
- ·Comfortable with Python or one general-purpose language but no production LLM/RAG experience
- ·Cloud fluency (Azure preferred, AWS/GCP acceptable) but not yet shipped agentic systems on customer infrastructure
- ·No structured methodology for problem framing, jobs-to-be-done, or AI-pattern selection in a client setting
- ·Limited fluency with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen) for real client workloads
- ·Cannot independently take a prototype to a production-grade, observable, cost-aware service with monitoring and red-team coverage
Where they'll arrive
- ✓Client discovery & solutioning runs discovery workshops, frames problems, scopes MVPs, maps business needs to AI patterns
- ✓Agentic AI & orchestration designs and builds multi-agent systems with LangGraph, CrewAI, and AutoGen on customer cloud
- ✓End-to-end build & deployment takes a solution from prototype to production-grade FastAPI service on Azure or AWS
- ✓Operationalisation & adoption instruments, monitors, red-teams, and drives user adoption post-deployment
- ✓Capstone-evidenced delivery ships a complete client-scenario solution evaluated by a joint NovelVista + client-side panel
- ✓FDE certification credential portfolio piece for client-facing AI engineering roles at services firms
Built for L&D outcomes, not seat counts.
Client discovery built in
FDE AI engineer course participants master discovery workshops, JTBD mapping, and MVP framing the skills that determine whether an engagement succeeds before a line of code is written.
Production RAG, not toy RAG
Learners build hybrid retrieval pipelines with re-ranking, grounding, and vector store selection the architecture pattern deployed in the majority of real enterprise AI engagements.
Agentic AI engineering depth
This agentic AI engineer training covers LangGraph, CrewAI, and AutoGen with hands-on labs that take a single-agent prototype through to a supervised multi-agent workflow on customer cloud.
Cost and observability ownership
Engineers learn semantic caching, model routing, OpenTelemetry tracing, and online eval pipelines the production economics skills that most AI bootcamps omit entirely.
AI red-teaming and security
Every cohort completes structured AI red-teaming training for engineers covering OWASP LLM Top 10, prompt injection, data residency, and responsible AI audit trails before client deployment.
Capstone-evidenced certification
The forward deployed engineer AI certification is awarded on panel-evaluated delivery a discovery doc, deployed service, monitoring dashboard, red-team report, and 90-day adoption plan.
A four-milestone path from skill gap to client-ready.
Foundation, discovery, and architecture
Learners establish a working mental model of the FDE seat, the 2026 LLM landscape, prompt engineering with eval harnesses, and client discovery culminating in a graded discovery doc and solution architecture for a mock client brief.
RAG pipelines and multi-agent AI systems training
Hands-on build weeks covering production RAG with hybrid retrieval and re-ranking, followed by multi-agent AI systems training using LangGraph, CrewAI, and AutoGen on Azure or AWS infrastructure.
Production build, observability, and security
Learners deploy a FastAPI service with streaming and auth, instrument it with OpenTelemetry and RAGAS eval pipelines, apply NeMo guardrails, and complete AI red-teaming training for engineers with a findings report.
Capstone and enterprise AI deployment training
The programme closes with enterprise AI deployment training in a full capstone scenario each FDE delivers a deployed RAG and multi-agent service, monitoring dashboard, red-team report, and 90-day adoption plan, evaluated by a joint NovelVista and client-side panel.
Want this curriculum aligned to your tech stack and project archetypes?
Why enterprise teams choose the B2B engagement model.
Trusted by Industry Leaders for Enterprise AI Upskilling
See why CEOs, CTOs, and business leaders collaborate with NovelVista
to discuss the future of AI, digital transformation, and workforce readiness.
- Exclusive AI leadership summits featuring enterprise decision-makers and technology experts
- Recognized corporate training partner for AI, Agile, DevOps, ITSM, and cybersecurity programs
- Trusted by organizations to build future-ready teams with practical, industry-focused learning
- Real conversations, real business challenges, and actionable AI transformation insights from industry leaders
Learn from domain experts with 15+ years of experience.
"My job isn't to produce engineers who can demo AI it's to build FDEs who can walk into a client account, frame the right problem, ship a production-grade solution, and own its adoption."
Taught by people who've actually shipped the work.
Built for L&D leaders and their learners.
Who this is for
- ·Senior developers and tech leads with 5+ years of experience moving into client-facing AI engineering roles at services firms
- ·Solution engineers and AI architects scoping and building production AI systems inside enterprise customer accounts
- ·Consultants and delivery leads at IT services organisations such as Capgemini, Wipro, Infosys, Accenture, HCL, and TCS who need to own AI engagements end-to-end
- ·Engineers enrolling in Forward Deployed Engineer AI corporate training to formalise their FDE capability with a panel-evaluated certification
- ·Organisations building or scaling a forward-deployed AI engineering bench for BFSI, healthcare, retail, and manufacturing client portfolios
Pre-requisites
- ·5+ years as a developer, tech lead, or solution engineer this is not an introductory AI course
- ·Working proficiency in Python or one equivalent general-purpose language used in production environments
- ·Cloud fluency in Azure (preferred), AWS, or GCP learners will deploy services on customer cloud infrastructure during labs
- ·Basic familiarity with REST APIs, containerisation concepts, and version control; no prior LLM or RAG experience required
Trusted by L&D leaders across the world.
"The discovery and scoping modules changed how our engineers walk into client accounts. They now frame the problem before reaching for a framework and that shift alone has improved our engagement outcomes."
"The RAG and agentic AI modules were genuinely production-grade. Our team shipped a hybrid retrieval service with re-ranking and a 3-agent workflow within two weeks of the programme closing."
"The red-teaming lab and security module gave our engineers a findings report format they could actually present to client InfoSec teams. That credibility is hard to build any other way."
Questions L&D teams ask before signing.
A Forward Deployed Engineer works directly with enterprise customers to design, deploy, customize, and operationalize production-grade AI systems and agent workflows.