Overview
Generative AI engineers build products powered by large language models: chatbots, copilots, AI agents, RAG systems, content generation pipelines. Since the ChatGPT inflection in late 2022, this has become one of the highest-paid and fastest-growing roles in Indian tech. Indian foundation-model startups (Sarvam AI, Krutrim, Ola Krutrim) and global capability centres (Microsoft Bangalore, Google Bangalore, OpenAI India) compete aggressively for talent.
Day-to-day responsibilities
Design prompt strategies for LLM-powered features; build RAG (Retrieval-Augmented Generation) pipelines using vector databases; fine-tune open-source LLMs (Llama, Mistral, Qwen) on domain data; evaluate model outputs against quality and safety benchmarks; build AI agent systems using LangChain or LlamaIndex; integrate LLMs with product backends (latency, cost, fallbacks); track and reduce hallucination rates; ship features end-to-end.
Skills required
- Python and JavaScript
- LLM APIs (OpenAI, Anthropic, Gemini)
- Vector databases (Pinecone, Weaviate, pgvector)
- LangChain or LlamaIndex frameworks
- Prompt engineering
- Fine-tuning (LoRA, QLoRA)
- Evaluation (Ragas, custom test sets)
- Production AI monitoring (LangSmith, Helicone)
Education path
B.Tech CSE or MTech with applied ML focus is the standard path. Many practitioners self-taught the LLM stack post-2023 from any software engineering background. Open-source contributions (Hugging Face, LangChain) are heavily weighted at hiring. Foundation-model research roles still favour MS or PhD from top institutes.
Career progression
- 1Gen AI Engineer (0-2 yrs)
- 2Senior Gen AI Engineer (2-5 yrs)
- 3Staff AI Engineer (5-8 yrs)
- 4Principal AI Engineer (8+ yrs)
- 5AI Architect / Founding AI Engineer
Top employers in India
Useful certifications
- Hugging Face NLP Course
- DeepLearning.AI Generative AI with LLMs
- LangChain Cookbook
- OpenAI Builder Series
- Anthropic Prompt Engineering Course