Gen AI/ LLM Engineer

ERM Placement Services; Ahmedabad District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

ERM Placement Services is seeking a GenAI Engineer to design, develop, and deploy scalable GenAI applications leveraging LLMs and agentic AI frameworks. The role focuses on building RAG pipelines, integrating foundation models into enterprise systems, and delivering API-backed Python services.

The candidate should be proficient in prompt engineering, model optimization, and collaborating with data, cloud, and product teams to ensure robust deployments.

Qualifications

• Hands-on experience building GenAI applications with LLMs.
• Experience with RAG pipelines and vector databases.
• Experience with enterprise workflow integration.
• Familiarity with API development and deployment in cloud.

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.

Skills

Python programming

Large Language Models (LLMs)

RAG architectures

Agentic AI frameworks

Prompt engineering

LLM orchestration

REST APIs

Cloud platforms

Tools

Pinecone

ChromaDB

FAISS

Weaviate

Milvus

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

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.