Gen AI/ LLM Engineer

ERM Placement Services; Indore District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

ERM Placement Services is seeking a GenAI Engineer with 2–8 years of experience to design and deploy advanced GenAI solutions in an enterprise setting. The role focuses on integrating LLMs, RAG pipelines, and autonomous AI frameworks into scalable workflows.

You will work on prompt engineering, model optimization, and building backend services in Python, coordinating with data, cloud, and product teams to deliver reliable AI-powered applications.

Qualifications

• Strong hands-on Python experience for GenAI applications.
• Experience building GenAI/LLM solutions for enterprise workflows.
• Proficiency with embedding models, vector search, and RAG pipelines.

Responsibilities

• Design, develop, and deploy GenAI applications using LLMs and Agentic AI frameworks.
• Build and optimize RAG pipelines with vector databases and embeddings.
• Develop AI-powered chatbots, copilots, and workflow automation tools.
• Integrate foundation models like GPT, Claude, Llama into enterprise systems.
• Work on prompt engineering, fine-tuning, and model optimization.
• Develop APIs and backend services using Python.
• Collaborate with data engineering, cloud, and product teams for scalable deployments.
• Implement monitoring and guardrails for GenAI applications.

Skills

Python

LLMs

RAG architectures

Agentic AI frameworks

vector databases

REST APIs

Tools

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.