Role & responsibilities

Generative & Agentic AI Engineer

Role summary

You will design and ship GenAI capabilities and agentic AI workflowsgrounded in NLP/Transformers—including RAG systems and advanced multiagent patterns. You’ll build secure, observable, and costaware LLM solutions on AWS/Azure, integrating with product backends and enterprise data.

Key responsibilities
Build GenAI services with robust prompt/tool use, function calling, and workflow orchestration; implement caching, retries, and token/cost controls.
Implement RAG pipelines (indexing, chunking, embeddings, rerankers) and evaluate retrieval/answer quality; progress to advanced agentic patterns (multitool, multistep, multiagent).
Apply NLP/Transformer techniques (finetuning, adapters/LoRA, distillation)



when justified by business and data constraints.
Engineer production Python services/APIs; integrate vector stores (FAISS, Pinecone), LangChain/LlamaIndex, streaming, and guardrails.
Operate solutions on AWS/Azure with proper observability, security, and governance hooks.

Musthave skills
GenAI foundations (LLMs, embeddings, prompting)
Transformers (Hugging Face ecosystem, finetuning strategies)
NLP applied skills (text processing, evaluation metrics)
RAG / advanced agentic AI design and implementation
Python, AWS/Azure
API development for modelbacked experiences

📌 Gen Ai Engineer Bengaluru (India)
🏢 EY
📍 India