ERM Placement Services
Gen AI/ LLM Engineer
Skills
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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