Gen AI/ LLM Engineer

ERM Placement Services; India; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

ERM Placement Services in Kolkata seeks a GenAI/LLM Engineer to design and deploy scalable GenAI applications. You will build RAG pipelines, integrate foundation models, and create AI-powered assistants within enterprise workflows. Strong Python and AI framework experience is required.

The role focuses on prompt engineering, model evaluation, and cloud-based deployment with collaboration across data engineering and product teams.

Qualifications

• 2–8 years of GenAI/LLM engineering experience.
• Hands-on Python development and API backends.
• Experience deploying GenAI in enterprise workflows.

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.
• Integrate foundation models like GPT, Claude, Llama into enterprise systems.
• Work on prompt engineering, fine-tuning, and model evaluation.
• Develop APIs and backend services using Python.
• Collaborate with data engineering, cloud, and product teams.
• Implement monitoring and guardrails for GenAI apps.
• Stay updated with GenAI advancements.

Skills

Python

LLMs

RAG

Agentic AI

LangChain

Vector databases

Prompt engineering

REST APIs

Cloud platforms

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.