Hinton AI Labs — AI writes the code now.
Companies still hire people who can ship it.
A 14-week, full-time program where you build a real AI product on a working engineering team.
You'll see inside the model layer by layer — then build with it: RAG, agents (LangChain and LangGraph), React, Python and data, inside a real codebase — directing AI coding agents, catching their mistakes, and shipping code that holds up in review.
Tokens
Text is split into tokens — whole words or word pieces — and each token is mapped to an ID number from a fixed vocabulary.
"Summarise" → [Sum][mar][ise] → [9127, 3876, 1082]
Cost, context limits and odd failures with numbers, names and Telugu or Hindi text all trace back to tokens.
Nobody hires you to start from an empty folder.
Start inside a working system
Day one begins inside a live, production-grade platform — built the way real teams build, with the trade-offs and edge cases to match.
Own it layer by layer
Learn a layer each week — backend, frontend, RAG, agents — and build it with your own code.
Work like the team you’ll join
Every task is a JIRA ticket, a branch, a pull request and a review.
14 weeks. One intelligent document platform, built piece by piece.
Every team builds the same architecture on a different domain — invoices, claims, lab reports, contracts or KYC — so every portfolio is unique.
Inside the codebase
Frontend
Backend
Processing, search and RAG
Agents and harness
Ship, sprint, interview
Inside the codebase
Clone a running system, read unfamiliar code and close your first bug tickets.
Frontend
Document list, upload, viewer and roles, wired to your real API.
Backend
Upload API, auth, storage, database and background jobs replace the backend mocks.
Processing, search and RAG
OCR, chunking, extraction, then keyword, vector, hybrid and agentic retrieval — plus how LLMs actually work.
Agents and harness
Tool calling, agent loops, memory, guardrails, MCP and human review.
Ship, sprint, interview
Dashboard and deployment, a live brownfield sprint, demo day and mock interviews.
Hireable three times over.
Interview-ready at three stages, not just at the end.
Full-stack developer
React and Python features shipped through Git and JIRA on a real codebase.
GenAI Developer
Document pipelines and multi-strategy retrieval you can explain and evaluate.
AI application engineer
Agentic systems with tools, guardrails, evals and cost control.
Trained to the roles our partners are hiring for.
We work alongside empanelled staffing firms and technology companies serving IT services and enterprise product teams. Graduates who clear demo day and mock technical interviews are put forward directly for partner roles.
Empanelled hiring partnerships with leading product engineering teams, GCCs, and high-growth AI companies across Hyderabad, Bengaluru, and remote teams.
Taught by people who build and hire.
Vijay Daggumati
CTO and architect with 15+ years across fintech, EV infrastructure, and government-scale platforms — with hands-on expertise in Gen AI, RAG, Agentic AI, AI Application Engineering, and Classical ML. Every module he designs is drawn from real delivery work, making the curriculum genuinely brownfield and battle-tested.
Manoj Kaushik
Fintech industry veteran with 18+ years, co-founder of Finmapp, and Head of Engineering at RuDo Wealth — with hands-on expertise in Gen AI, LLMs, RAG, Agentic AI, AI Application Engineering, and DevOps. He brings end-to-end credibility across WealthTech product building, scalable fintech infrastructure, and engineering production-grade intelligent applications.
Everything you need to know.
Have a specific question not covered here? Reach out directly to our admissions team on WhatsApp.
How is Hinton AI Labs different from other bootcamps or online courses?
Most courses have you build toy to-do apps from scratch in isolation. At Hinton, you start on day one inside a running, messy brownfield document platform full of mocks and intentional bug tickets. You learn by picking up JIRA tickets, opening PRs, running CI test suites, and replacing backend mocks layer-by-layer with production code, vector search, RAG pipelines, and agent harnesses.
What is the schedule and structure of the 14-week program?
The program is 14 weeks, full-time (approximately 6 hours per day). Core sprint work and architecture lectures run hybrid, with designated in-person collaborative sprint days, live code reviews, and demo days at our centre in Hyderabad.
What background or prerequisites do I need?
You need solid foundational programming experience in either Python or TypeScript/JavaScript (loops, functions, data structures, and basic HTTP/APIs). You do not need prior machine learning or deep learning experience — we teach LLM architecture and AI engineering from first principles.
What are the three hiring checkpoints?
Rather than waiting until the end to become hireable, you reach three distinct industry-ready stages: Full-stack developer after 8 weeks (FastAPI, Postgres, React, TypeScript, Git), RAG engineer after 11 weeks (document ingestion, hybrid search, reranking, evals), and complete AI application engineer after 14 weeks (agents, tool calling, MCP, guardrails, production deployment).
How does the placement process work?
We work alongside empanelled staffing firms and technology partners serving enterprise IT services, Global Capability Centres (GCCs), and product startups. Candidates who clear weekly sprint goals, brownfield delivery milestones, demo day, and mock technical interviews are put forward directly for partner interviews.
How do I apply and get started?
Fill out the simple application form with your name, WhatsApp number, and academic or professional background. Our admissions team reviews applications on a rolling basis and reaches out directly on WhatsApp to confirm your seat and guide you through batch onboarding.
Why the name "Hinton AI Labs"?
We named our lab with deep gratitude in honour of Dr. Geoffrey Hinton — Nobel laureate in Physics and Turing Award winner, widely celebrated as the "Godfather of AI". His decades-long dedication to artificial neural networks and backpropagation laid the foundation for modern deep learning and large language models. Hinton AI Labs exists to instill that same curiosity, rigor, and first-principles thinking in the next generation of AI engineers.
Applications open for the upcoming cohort.
14 weeks, full-time (about 6 hours a day). In-person collaborative sprint days and demo days at our Hyderabad centre.