GenAI Engineering Foundations to Production
A 16-week, job-ready program for engineering graduates.
From zero AI experience to a portfolio-ready, production-style capstone.
Weeks
16
Training hours
144
Hands-on labs
~60%
Capstone options
10+
Program introduction
AI is moving from prompts to autonomous systems. Most training programs stop at ‘how to prompt ChatGPT.’ The gap between that and an engineer who can actually design, evaluate, secure, and ship an AI system into production is where careers get stuck before they start.
This 16-week program is built for final-year engineering students and recent graduates who want to enter the job market as GenAI-ready engineers: not just people who know how to use an AI chatbot, but people who can design, build, test, and ship real AI systems. You will learn to work with LLMs, Retrieval-Augmented Generation (RAG), AI agents, workflow orchestration, evaluation frameworks, and industry-relevant tools, and graduate with a deployable, defensible capstone project.
Why choose this program
Starts from zero, no prior AI experience assumed, and ends with a portfolio-ready, production-style capstone project.
Covers the full stack employers actually screen for: prompting, RAG, agentic AI, evaluation, security, deployment, and MLOps, not just prompting.
Every theory week is paired with a hands-on lab in the same week, so concepts get applied immediately, not just memorized.
Iterative RAG build (v1 to v2) so you learn to evaluate and improve like a real engineer, not just ship once.
Includes dedicated employability weeks: resume strategy, mock interviews, and a real industry panel viva, so you leave interview-ready, not just skill-ready.
What you will build
A working RAG assistant with citations and grounded, hallucination-resistant answers, built twice (v1 and an optimized v2) so you learn to iterate like a real engineer.
An MCP-enabled AI agent with multiple tools, guardrails, and safe fallback behavior.
A multimodal pipeline handling images, OCR, and audio/video.
A full production-style capstone: choose from real enterprise scenarios like a policy-answering Knowledge Bot, a Contract Clause Copilot, a Support Triage Router, or a Multi-Agent Research-to-Brief Factory.
Systems stack you’ll master
Intelligence & reasoning layer
Leading LLMs (OpenAI, Anthropic) as the reasoning engine behind your applications.
Knowledge & retrieval layer
LangChain, embeddings, vector stores, and grounded RAG pipelines.
Agent orchestration layer
Model Context Protocol (MCP)-based agents, with an introduction to n8n-style workflow automation and CrewAI multi-agent patterns.
Evaluation & reliability layer
Golden datasets, rubric grading, regression testing, hallucination and bias checks, tracing (LangSmith, OpenTelemetry).
Deployment & MLOps layer
API service patterns, secrets management, CI for evals, release gates, and rollback strategy.
Who should apply
Final-year engineering students preparing to enter the job market.
Recent graduates (0 to 2 years of experience) who want a structured, portfolio-first path into AI engineering roles.
Anyone comfortable with basic programming who wants to build real, working AI systems, not just use AI tools.
THE OUTCOME
Turn skills into career-ready roles
GenAI / LLM Engineer
Building and deploying LLM-powered applications, RAG systems, and knowledge bots.
Junior Agentic AI Engineer
Contributing to autonomous agent workflows under senior guidance.
AI Application Developer
Turning LLM, RAG, and agent workflows into working, user-facing products.
ML/AI Associate Engineer
Supporting production AI systems with a foundation in evaluation and deployment practices.
Meet your trainers
This program is designed and delivered by senior engineering leaders who have built and shipped real products, not full-time trainers reading from slides.
Arun Tiwari
Senior Consultant & Trainer | B.Tech, IIT (BHU) Varanasi
An IIT graduate (B.Tech, 2000, IIT-BHU) and product-oriented technology leader with around 24 years of experience across all aspects of product engineering, for both startups and enterprises.
Rahul Singh
Senior Consultant & Trainer | B.Tech, IIT (BHU) Varanasi
A senior engineering leader with over 20 years of experience in IT, specializing in digital transformation programs across all stages of the software lifecycle, with expertise in Cloud Computing, Microservices, Event-driven Architecture, Big Data, and Generative AI.
Graduating? Become an AI-ready engineer in 16 weeks.
Go from zero to a real capstone project and build the skills companies hire for.
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