AI companies are hiring engineers who deploy with the customer
The pattern across AI-first companies: engineers embedded with customers to build and ship real solutions, not just features.
Incrito Pro · 8-month cohort · Interview guarantee
AI ForwardDeployed Engineer
Applied GenAI, agents & client delivery
AI engineering and client-facing consulting in one curriculum, built around real client projects — from the first discovery call to deploying and scaling solutions in production.
Graduates go on to build and deploy AI at teams like these
01The role
What a Forward Deployed Engineer actually does
Part software engineer, part solutions architect, part customer partner. FDEs are who AI companies send in when a deployment has to work in the real world — messy data, security constraints, non-technical stakeholders and a deadline.
Build the integration
Stand up full-stack services, pipelines and UIs that connect a model to the customer's systems and data.
Wire in the AI
Prompt design, RAG, evals, tool-calling and guardrails — make the model reliable for one specific business problem.
Tame the data
Ingest, clean and model whatever the customer has — SQL, files, APIs, event streams — so the system has something to reason over.
Work the room
Run discovery with stakeholders, scope ruthlessly, demo every week and hand over something the customer's team can operate.
Ship it safely
Auth, tenancy, logging, cost controls and a rollback plan — production from day one, not a notebook.
Prove the value
Instrument outcomes, tie them to a metric the customer cares about, and turn a pilot into a renewal.
02The industry signal
Why the Forward Deployed Engineer is AI's next career path
The Forward Deployed Engineer, explained
A hybrid of software engineering and solutions delivery — and one of the fastest-growing roles in applied AI.
Demand for applied-AI delivery talent is climbing fast
Job postings mentioning forward-deployed or applied-AI engineering have risen sharply over the past year.
03Outcomes
Where this program takes you
Build fast, integrate AI, talk to customers — that combination is what AI-first companies and consultancies are hiring for right now.
- 3×
- Interview call-backs vs a generic SWE profile
- 5+
- Guaranteed hiring-partner first-rounds
- 40+
- Hiring partners in the network
Roles you can target
Forward Deployed EngineerAI Solutions EngineerApplied AI EngineerSolutions Architect (AI)Implementation EngineerAI Delivery Consultant
Typical compensation
₹18–40 LPA in India · $120–180K abroad for experienced FDEs
Hiring-partner network
04Curriculum
8 months, eight shipped deployments
Eight months, eight modules. Every module ends with something you deploy and demo to a mentor panel — no passive lectures. The final module rolls straight into the interview guarantee.
Module 1 - Engineering foundations for AI delivery
Everyone starts from the same baseline. Build a small full-stack app, containerise it, wire in auth and multi-tenancy, and ship it with one command — the muscle memory every deployment is built on. You also practise dropping into an unfamiliar codebase and mapping a customer's stack under time pressure.
Project: Multi-tenant service with auth, deployed to a cloud environment
Topics covered
Build
- Modern TypeScript full-stack — Next.js, APIs, Postgres
- Containers, environments and one-command deploys
- Auth, multi-tenancy, secrets and config
Read the room
- Working through an unfamiliar codebase fast
- Mapping a customer's stack, data and constraints
Module 2 - LLM systems that hold up
Make a model reliable for one real business problem: retrieval that actually retrieves, structured outputs you can trust, evals that catch regressions before users do, and latency and cost you can defend to a customer.
Project: Support copilot with retrieval, structured output and an eval suite
Topics covered
Model layer
- Prompt and context engineering, structured outputs
- RAG — chunking, embeddings, retrieval quality, rerankers
Make it reliable
- Evals, golden sets and regression tests
- Latency, streaming, caching and cost control
Module 3 - Agents and tool use
Move from a single call to a system that takes actions. Tool calling, agent loops that actually terminate, planning across steps, and human approval gates for anything that touches production.
Project: Workflow agent that runs a multi-step task across three systems with approval gates
Topics covered
Agent design
- Tool calling, function schemas and error handling
- Loops, planning and termination conditions
Keep it safe
- Human-in-the-loop approvals and audit trails
- Guardrails, allow-lists and blast-radius limits
Module 4 - Data plumbing
Whatever the customer has — SQL, spreadsheets, APIs, event streams — get it clean, modelled and flowing so the system has something trustworthy to reason over. Includes text-to-SQL behind a guardrail layer.
Project: Document-to-database pipeline with validation and lineage
Topics covered
Ingest
- Sources — SQL, files, APIs and event streams
- Schema modelling and normalisation
Move it
- Batch and incremental pipelines
- Data-quality checks, lineage and text-to-SQL guardrails
Module 5 - Production, security and observability
Run it like it's someone else's business — because it is. Tenancy and secrets in depth, cost controls, logs, traces and dashboards, SLOs and on-call basics, a security review you can pass, and a rollback plan you have actually tested.
Project: An instrumented, security-reviewed deployment with dashboards and a rollback runbook
Topics covered
Operate
- Logging, tracing, metrics and dashboards
- SLOs, alerting and incident response
Harden
- Threat modelling and security review
- Cost controls, rate limits and rollback plans
Module 6 - The deployment craft
The non-code half of the job. Run discovery with stakeholders, scope ruthlessly, demo every week, write runbooks, hand over something the customer's team can operate — and turn a pilot into a renewal with a value memo.
Project: Discovery-to-handover simulation with a mentor playing the customer
Topics covered
Deliver
- Discovery calls and ruthless scoping
- Weekly demo cadence and stakeholder comms
Hand over
- Runbooks, docs and training the customer's team
- Value memos and turning a pilot into a renewal
Module 7 - Capstone deployment
A realistic five-week brief with a mentor playing the customer. Discovery, weekly stakeholder demos, a security review, handover documentation, and a value memo tied to a metric the customer cares about. This is the piece hiring managers actually read.
Project: A full customer deployment plus a value memo tied to a real metric
Topics covered
Weeks 25–27
- Discovery, scoping and architecture sign-off
- Build with weekly stakeholder demos
Weeks 28–29
- Security review and handover documentation
- Outcome instrumentation and the value memo
Module 8 - Interview and offer sprint
Turn eight months of shipped work into offers. FDE-style case interviews and take-homes, system design for applied AI, tight deployment write-ups, and mock loops with hiring partners. Clear the bar here and the interview guarantee kicks in.
Project: A portfolio and three deployment write-ups, plus entry into the guaranteed-interview pipeline
Topics covered
Prepare
- FDE case interviews and take-homes
- System design for applied-AI delivery
Present
- Portfolio and deployment write-ups
- Mock loops with hiring partners and feedback
05Projects
What you'll have built by the end
Eight deployable projects, each with a demo video and a write-up you can send a hiring manager.
Multi-tenant service foundation
The base every deployment starts from: a multi-tenant service with auth, config and one-command deploys, running in a real cloud environment.
Full-stackMulti-tenantDeploys
Support copilot for a B2B SaaS
RAG over docs and tickets, tool-calling into the CRM, an agent that drafts replies and escalates. Deployed multi-tenant with usage limits.
RAGAgentsMulti-tenant
Workflow agent with approval gates
An agent that runs a multi-step internal workflow across three systems, with human approval gates and a full audit trail.
Workflow agentIntegrationsApprovals
Document-to-database pipeline
Ingest messy PDFs and spreadsheets, extract structured records with an LLM, validate, and load into Postgres with lineage.
ExtractionData pipelinesEvals
Analyst assistant over a warehouse
Natural-language questions to validated SQL to charts, with a guardrail layer and a feedback loop.
Text-to-SQLGuardrailsBI
Production hardening pack
Dashboards, traces and SLOs for a live AI service, a security review you pass, and a rollback runbook you have rehearsed.
ObservabilitySecuritySLOs
Eval harness and scorecard
A reusable evaluation framework with regression tests, a dashboard and CI gating.
EvalsCIObservability
Capstone: full customer deployment
The four-week build — discovery, weekly demos, security review, handover docs and a value memo tied to a metric.
End-to-endDeliveryValue memo
06Mentors
Learn from engineers building in the real world
Practising Forward Deployed Engineers, applied-AI engineers and solutions architects. They review your work 1:1 and play the customer in your capstone.
07The Incrito Pro method
The foundation behind every deployed-engineer offer
Structured Curriculum
A step-by-step roadmap designed by working Forward Deployed Engineers — full-stack foundations, applied AI, agents and client-facing delivery, in the order real deployments demand.
Module 1: Engineering foundations for AI delivery
Module 2: LLM systems that hold up
Module 3: Agents and tool use
1:1 Expert Mentorship
1:1 reviews every week with practising FDEs and applied-AI engineers who guide your projects and play the customer in your capstone.
Placement Support
Runs from your final month until you're placed — no time limit.
- A resume that stands out to hiring managers
- LinkedIn and portfolio optimisation
- Mock interviews with mentors
- Job applications and referral guidance
- 40+ hiring partners and warm referrals
Live Classes (Assignments + Projects)
Learn from engineers shipping AI in production, work through guided assignments, and build client-style projects end to end.
Multi-tenant service foundationSupport copilot with RAG + evals
Full customer deployment — capstone08Who it's for
Built for engineers who want to be in the room
This program is for you if
- Software engineers with 1–5 years' experience who want an AI-heavy, customer-facing role
- Backend and full-stack devs who like scoping and demos, not just tickets
- Data engineers who want to own the model layer, not only the pipeline
- Consulting engineers moving into applied-AI delivery
What you’ll need coming in
- Comfortable in one modern language and able to build a small web app end to end
- Basic SQL and REST APIs
- Git, the command line and reading unfamiliar code
- No prior ML required — we cover the AI layer from first principles
09Cohort and pricing
The next cohort
Small cohorts, so every project gets mentor time. Apply early — seats are limited.
Next start
Starts the first Monday of every month
Format
Live online · two evening sessions a week + weekend labs
Length
8 months (32 weeks) + interview guarantee + job assistance until placed
Program fee
Request the fee & apply Shared on a 20-minute call
You'll get the exact fee on your call — along with any scholarship, no-cost EMI or income-share option you qualify for. No obligation.
What’s included
- 1:1 mentor reviews every week for eight months
- Eight shipped deployments for your portfolio
- Capstone with a mentor playing your customer
- Interview guarantee — 5+ hiring-partner first-rounds or a full refund
- Job assistance until you're placed: referrals, mock loops, negotiation
- Lifetime access to recordings and the alumni network
Interview guarantee. Finish the program and clear the mock-interview bar, and we guarantee 5+ hiring-partner first-round interviews within 6 months of completing the program — or a full refund. Job assistance then continues until you’re placed.
10Apply now
Start your application
11Alumni
From the last cohorts
I came from backend work. The capstone was the closest thing to a real deployment I'd done — discovery, weekly demos, a security review. That's what got me through the interviews.
The AI modules are practical, not academic. RAG, evals, guardrails, cost — the stuff that actually breaks in production. I use all of it day to day.
Mentor reviews every week kept me honest. My write-ups from the program are still what I show hiring managers.
12FAQ
Questions, answered
Do I need machine-learning experience?
No. You need to be a capable software engineer. We teach the AI layer — prompting, RAG, agents, evals — from first principles. If you can build a web app and write SQL, you can keep up.
How much time per week?
Plan for 12–15 hours across the eight months: two live evening sessions, a weekend lab, and project work. The capstone weeks are heavier.
Is it live or recorded?
Live cohort. Sessions are recorded for revision, but mentor reviews, demos and the capstone are all real-time.
How does the interview guarantee work?
Complete the program, pass the capstone mentor review and clear the mock-interview bar in the final sprint, and we guarantee at least 5 first-round interviews with hiring partners within 6 months of completing the program — or we refund your full fee. It is an interview guarantee, not a job guarantee: no one can honestly promise the offer itself.
What does job assistance include?
It starts in your final month and runs until you are placed, with no time limit: portfolio and write-up reviews, FDE-style mock interviews, warm referrals into the 40+ hiring-partner network, and offer-negotiation help.
What do I have to do to qualify for the guarantee?
Attend the live sessions, submit every module project, pass the capstone mentor review, and clear the mock-interview bar in Module 8. Fall short on those and we will still support you — you just will not be covered by the refund clause.
How much is the fee, and can I pay in instalments?
We share the exact fee on a short call, together with any scholarship, no-cost EMI or income-share option you qualify for. That way the number you hear already reflects what applies to you.
Next cohort filling now
Apply to the Forward Deployed Engineer program
A short application and a 20-minute call. If it's a fit, you'll get an offer and a start date within a week.