Is Generative AI a real career in India in 2026 or just hype?

It is a real, well-paying career. As of early 2026, LinkedIn India lists 4,800+ Gen AI / LLM engineer roles. Indian product companies (Razorpay, CRED, Zerodha, Meesho) are hiring aggressively, and salary ranges reflect the supply gap: ₹8–24 LPA depending on experience and depth.

What is the difference between Generative AI and Agentic AI?

Generative AI is using an LLM to produce content (text, code, images). Agentic AI is using an LLM as the planner inside a system that calls tools, holds state, recovers from errors, and completes multi-step workflows. Senior roles increasingly hire for agentic skill.

Will I learn ChatGPT, Claude, or both?

Both. We teach the OpenAI API and the Anthropic Claude API deeply. The fundamentals transfer, and we explicitly teach the judgement of which to pick per task — Claude for long-context analysis, GPT-4o for tight latency, structured outputs from either.

Do I need a data science background to take this course?

No. Solid Python is required, but you do not need to know classical ML. The course is engineering-first — building systems that use LLMs, not training LLMs from scratch.

What is the AI engineer / LLM engineer salary in India?

Our 2025 cohort offers ranged from ₹8 LPA (fresher at a service company) to ₹24 LPA (mid-senior at Razorpay / CRED). Median was ₹14 LPA. With 2 years of LLM engineering experience, ₹30+ LPA is reachable at Indian product companies.

Will I build real production projects or just toy examples?

Real production projects. Module 2 includes a 50k-document RAG system. Module 3 includes a multi-agent workflow. Your capstone (Module 5) is a problem of your choice, built to production standards and shipped publicly.

How does this course handle API costs?

We cover up to $30 of API credits per student through our partnership tier with OpenAI and Anthropic. We also teach prompt caching, model routing and cost-aware design — the same engineering you would do in production.

Is LangChain still relevant given how much it changes?

Yes — and that is exactly the skill we teach. LangChain and LangGraph are the most-used frameworks in 2026, but the underlying patterns (agents, tools, RAG, evals) are what matters. We teach the patterns; the framework is interchangeable.

Can I take this course while working full-time?

Yes. Live sessions are 3 evenings a week (7–9pm IST) plus weekend office hours. Plan for 12 hours a week. About 70% of our Gen AI cohort are working professionals — many switching from non-ML engineering.

What is the placement support like for Gen AI roles specifically?

Our hiring panel includes Gen AI / ML engineers at Razorpay, CRED, Observe.AI, NVIDIA and Indian AI startups. We make direct introductions, run system-design mocks calibrated to product-company bars, and continue support for 90 days post-graduation.

Future-Proof

Gen AI & Agentic AI

Name: Gen AI & Agentic AI
Price: 45000 INR
Availability: InStock

India's deepest Generative AI program. Three months of building multi-agent systems with LangChain, LangGraph, Claude and OpenAI — for hiring teams who pay ₹8–24 LPA.

LangChainLangGraphRAGOpenAIClaude

3 months ₹8–24 LPA Max 15 students

Program at a glance

Duration: 3 months
Cohort size: Max 15 students
Placement rate: 85%
Salary range: ₹8–24 LPA
Format: Live online + Hyderabad lab
Certificate: Verifiable + GST

Try a free masterclass firstSee enrolment options ↓

Next cohort: 30 May 202615 seatsLimited to 15 students 4.9 rating

Why this program, for the Indian market

The "Generative AI engineer" role barely existed two years ago. In 2026, every Indian product company — Razorpay, Zerodha, CRED, Meesho, Swiggy, Flipkart and dozens more — is hiring engineers who can ship LLM-powered features that actually work in production. The supply of qualified candidates is tiny. The salary range reflects that: ₹8 LPA at entry, ₹24+ LPA for senior agentic engineers.

The Nettms Gen AI & Agentic AI program is built for that gap. Three months of building real systems — RAG pipelines that scale, multi-agent workflows with proper state management, evals that catch regressions before users do, and the cost + latency engineering that turns a demo into a product. We teach with LangChain, LangGraph, OpenAI, Claude and HuggingFace — the actual stack senior teams use.

You leave with three shipped projects in your GitHub: a production RAG system, a multi-agent workflow agent, and a capstone problem of your choice. Plus the system-design intuition for "how do I keep this under $200/month at 1000 users" which is the question every hiring panel actually asks. Our cohort is capped at 15, mentored by engineers currently shipping LLM features at Indian product companies.

Graduates have been placed at

$fractal$
$fractal$

· and 50+ more partners across India, UAE and the UK

Who this is for

Built for these candidates

Software engineers (Python, Node, Java) ready to specialise into LLM engineering.
Data scientists wanting to move from classical ML into agentic systems.
Senior engineers at service companies looking for a product-company switch.
Founders or builders who want to ship AI features that survive production.

Prerequisites

What you need on day one

Solid Python — comfortable with functions, async, classes and pip.
Basic understanding of HTTP and REST APIs.
A laptop with stable internet — model API calls happen live.
12 hours per week for 12 weeks.

Live cohorts · 15 students max

Built around projects, not lectures.

What you'll learn

Every outcome here is a thing hiring managers test for. Not a slide you'll see once and forget — a skill you'll build in a project.

Build production-grade RAG systems that scale to 100k+ documents.
Master Claude and OpenAI tool use, structured outputs, and prompt caching.
Ship multi-agent systems using LangGraph state machines.
Evaluate agents with LangSmith and custom Python evals.
Engineer for cost — keep an agent under $0.10 per session at scale.
Build embedding pipelines with hybrid search (BM25 + vector).
Implement guardrails — prompt injection defence, PII redaction, content moderation.
Deploy agents on AWS Lambda + Vercel + Modal with cold-start engineering.
Run an LLM eval harness — regression-test your prompts like code.
Pass live coding rounds at Razorpay, CRED, Zerodha and Gen-AI startups.
Read and implement the latest OpenAI / Anthropic capability releases within a week.
Build a public Gen AI portfolio that recruiters share inside hiring teams.

Free · 90 minutes · live

Ship a working AI agent before you decide

Join our free "Build Your First AI Agent in 90 Minutes" masterclass. Live coding, real Claude API, working agent at the end. Then judge whether the paid cohort is right for you.

Reserve a free seat →

Curriculum · Program • GEN-AI

A complete program, module by module.

12 modules · 4 Months · 16 Weeks · 130+ Hours · Intermediate to Advanced.

A hands-on, project-driven program that takes you from Generative AI fundamentals through to building autonomous multi-agent systems. You will master LangChain, LangGraph and the Hugging Face ecosystem, build and deploy real RAG pipelines, and graduate with the skills companies are actively hiring for in the agentic AI era.

Duration
4 Months · 16 Weeks
Hours
130+ Hours
Level
Intermediate to Advanced
Tools & stack
LangChain, LangGraph, Hugging Face, OpenAI, Pinecone

Fundamentals of generative models, how they differ from traditional ML, the transformer revolution, and the practical applications transforming every industry.

Prefer to read the full brochure offline? Use the Download curriculum button above — we'll send a one-time code to your phone and unlock the PDF instantly.

Who should enroll

Designed for ambitious learners.

AI/ML Engineers and developers building advanced agent workflows
Data Scientists integrating agentic behavior into their projects
Software Engineers orchestrating multi-agent systems with modern frameworks
NLP practitioners moving into the agentic era
Technical entrepreneurs and innovators building AI-native products
Students and academics eager to work at the frontier of AI

Real outcomes, not just hours

Why this program.

Hands-on, project-based
Real agent applications, not toy demos.
Frontier-ready curriculum
LangGraph, RAG and multi-agent patterns.
Cutting-edge tooling
The exact stack companies are hiring for in 2026.
Cloud & on-premise deployment
Ship to production, not just to notebooks.
Portfolio of real agents
RAG, research and domain assistant builds.
Direct path to AI engineer roles
Curriculum mapped to live job descriptions.

Indicative salary by role · India 2026

From classroom to offer letter.

Gen AI Developer₹8.0 – 15.0 LPA
LLM Application Engineer₹10.0 – 20.0 LPA
AI Engineer (Agentic)₹12.0 – 25.0 LPA
Prompt & RAG Engineer₹9.0 – 18.0 LPA
Senior AI Engineer₹20.0 – 35.0 LPA
AI Architect / Lead₹30.0 – 60.0 LPA

Placement support

100% placement assistance with leading AI-first companies
Resume rebuilds focused on AI engineering portfolios
Mock interviews on system design, RAG and agent architecture
Live LLM and LangGraph coding interview practice
Direct introductions to hiring partners building Gen AI products
Open-source contribution and portfolio mentorship

Indicative annual compensation, India market • 2026

Tools you'll master

The exact stack, with the why behind each choice

LangChain
The Gen AI Lego kit. Chains, tools, retrievers, parsers.
LangGraph
State machines for agents — what production teams actually use.
OpenAI API
GPT-4o + structured outputs + function calling deep dive.
Claude API
Anthropic's API — tool use, prompt caching, vision, code execution.
LangSmith
Observability and evals — debug what your agents actually did.
Pinecone / pgvector
Vector stores — when to pick which, scaling tradeoffs.

Capstone projects

Real projects, real datasets, public portfolio

01Multi-agent research analyst — browses, reads, writes a structured report.
02Production RAG over 50k internal documents with hybrid search and citations.
03Autonomous customer support agent with human handoff and CSAT eval.
04AI sales-development agent for B2B SaaS — generates outreach, runs sequences.

Where the work continues

From cohort to production team in 60–90 days.

Career outcomes

Where graduates work — and what they earn

Salary range (India)

₹8–24 LPA

Placement rate

85%

Avg. time to offer

60 days after graduation

Roles you can target

Generative AI Engineer
AI Engineer
LLM Engineer
Agent Developer
AI Product Engineer
Applied AI Engineer
Founding Engineer (AI startups)

Cities hiring now

Bengaluru
Hyderabad
Mumbai
Pune
Gurgaon
Remote

Hiring partners

Razorpay
CRED
Zerodha
Meesho
Swiggy
Observe.AI
Needl AI
NVIDIA
Google
Amazon
Fractal
Tredence

Why students pick Nettms for Gen AI & Agentic AI

01
Curriculum updated within 6 weeks — Anthropic and OpenAI ship every month.
02
Mentors are currently shipping LLM features at Razorpay, CRED and AI startups.
03
We cover up to $30 of LLM API credits per student — no surprise bills.
04
Built around evals, not vibes — your agents get regression tests.
05
Smallest cohort of any Gen AI program in India — max 15 students.

Upcoming cohorts

Batch	Starts	Mode	Seats left
Gen-AI-Batch-3	30 May 2026	hybrid	6 of 15	Enrol

Mentors

Nettms Admin

Mentor

Frequently asked questions

The questions students from Hyderabad, Bengaluru, Pune, Mumbai and 30+ cities ask before enrolling.

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Investment & enrolment

Three flexible ways to join the next cohort

No-cost EMI, instant referral discount, and a 7-day no-questions-asked refund. Every payment includes a GST invoice and lifetime access to recordings.

Option 1 · One-time

₹45,000

Pay once, lock the seat. Save 5% with a referral code at checkout.

Enrol with one-time payment

No-cost EMI

Option 2 · 3-month EMI

₹15,000/mo

Zero interest. Auto-debited monthly. Major Indian banks supported via Razorpay.

Start no-cost EMI

Option 3 · Referral

Save ₹15,000

Any current Nettms student can refer you. The discount applies instantly at checkout — no codes to chase.