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Gen AI/ LLM Engineer

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Onsite

Gen AI/ LLM Engineer

ERM Placement Services

Gen AI/ LLM Engineer

Skills

Data EngineeringPythonMicroservicesAINo-code Automations

2 months ago

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Important information


Contract type:

Permanent

Location:

Bhubaneswar, Odisha, India

Work mode:

Onsite

Published on:

31 August 2026

What they need


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 Python programming.
  • Experience with Large Language Models (LLMs) and GenAI ecosystems.
  • Strong understanding of RAG architectures, embeddings, vector search, and semantic retrieval.
  • Experience with Agentic AI frameworks such 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.

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