Gen AI/ LLM Engineer

ERM Placement Services; Gurugram District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

ERM Placement Services is seeking a GenAI/LLM Engineer to design, develop, and deploy AI-driven applications. The role focuses on integrating LLMs, building RAG pipelines, and delivering AI-powered assistants and automation within enterprise workflows.

Ideal candidates will have hands-on Python development with strong GenAI ecosystem experience, vector databases, and API-backed microservices. Collaboration with data, cloud, and product teams is essential for scalable deployments.

Qualifications

• Hands-on Python development with GenAI experience.
• Experience building scalable GenAI applications and enterprise integrations.
• Familiarity with vector databases and embeddings.
• Experience with deployment and monitoring of GenAI systems.

Responsibilities

• Design, develop, and deploy GenAI apps using LLMs and Agentic AI.
• Build and optimize RAG pipelines with embeddings and vector stores.
• Develop AI-powered chatbots and workflow automations.
• Integrate foundation models into enterprise systems.
• Implement monitoring and guardrails for GenAI apps.
• Collaborate with data, cloud, and product teams for deployment.
• Work on prompt engineering and model tuning.

Skills

Python programming

LLMs

RAG architectures

Vector databases

Prompt engineering

REST APIs

Cloud platforms

LLM orchestration

Agentic AI

Tools

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

Pinecone

ChromaDB

FAISS

Weaviate

Milvus

Job description

Job Description GenAI / LLM Engineer

Experience:2–8 Years
Work Locations:Kolkata

We are looking for skilled and passionate GenAI Engineers with strong experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and Python development. The ideal candidate should have hands‑on experience building scalable AI applications, integrating LLMs into enterprise workflows, and developing intelligent autonomous systems.

Key Responsibilities

• Design, develop, and deploy GenAI applications using LLMs and Agentic AI frameworks.
• Build and optimize RAG pipelines using vector databases and embedding models.
• Develop AI-powered chatbots, copilots, assistants, and workflow automation solutions.
• Integrate foundation models such as GPT, Claude, Llama, Gemini, or similar into enterprise systems.
• Work on prompt engineering, fine‑tuning, evaluation, and model optimization.
• Develop APIs and backend services using Python.
• Collaborate with data engineering, cloud, and product teams for scalable deployments.
• Implement monitoring, guardrails, and performance tuning for GenAI applications.
• Stay updated with advancements in GenAI, autonomous agents, and AI tooling ecosystems.

Required Skills

• Strong hands‑on experience in Pythonprogramming.
• Experience with Large Language Models (LLMs)and GenAI ecosystems.
• Strong understanding of RAG architectures, embeddings, vector search, and semantic retrieval.
• Experience with Agentic AI frameworkssuch as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
• Hands‑on experience with vector databases like Pinecone, ChromaDB, FAISS, Weaviate, or Milvus.
• Experience in prompt engineering and LLM orchestration.
• Familiarity with REST APIs, microservices, and cloud platforms.
• Good understanding of AI application deployment and scalability.