LLM / Agentic AI Engineer

6 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Role Overview

strategic and hands-on role

 

Key Responsibilities

  • Design, fine-tune, and evaluate

    Large Language Models (LLMs)

    for agent-based reasoning, natural language interaction, and workflow orchestration.
  • Build

    autonomous agents

    using frameworks like

    LangChain

    ,

    AutoGen

    ,

    CrewAI

    , or similar, integrated with tool use, memory, and multi-step planning.
  • Implement

    Agentic Frameworks and Digital Twins

  • Develop and optimize

    Retrieval-Augmented Generation (RAG)

    pipelines using

    vector databases

    (e.g., FAISS, Weaviate) and hybrid architectures like

    GraphRAG

    .
  • Engineer agent workflows with

    tool calling

    ,

    multi-agent collaboration

    , and

    long-term memory (episodic + semantic)

    .
  • Monitor and improve performance metrics like reasoning accuracy, hallucination rate, and latency under production constraints.
  • Collaborate with DevOps, product, and platform teams to scale agents using Docker, Kubernetes, and Azure ML.

 

Must-Have Skills

  • 3–6 years of experience in

    LLM-based NLP / AI

    roles, with hands-on deployment experience.
  • Proficiency in

    LangChain

    ,

    AutoGen

    ,

    CrewAI

    , or similar agent frameworks (real-world examples preferred).
  • Strong understanding of

    agent memory

    ,

    task planning

    , and

    function/tool calling workflows

    .
  • Experience with

    RAG pipelines

    ,

    embedding models

    , and

    vector search systems

    .
  • Deep knowledge of

    Transformers

    ,

    Hugging Face ecosystem

    , and custom prompt engineering.
  • Proficiency in

    Python

    and ML libraries like PyTorch, TensorFlow.
  • Familiarity with

    knowledge graphs

    ,

    enterprise data systems

    , and orchestration strategies.

 

Preferred Qualifications

  • Experience designing

    persona-aware agents

    for enterprise use cases (BFSI, healthcare, public sector).
  • Familiarity with

    BertGraph

    ,

    GraphRAG

    , or similar graph-augmented architectures.
  • Experience with

    Azure AI Studio

    ,

    OpenAI APIs

    ,

    Anthropic Claude

    , or

    Meta LLaMA

    models.
  • Background in agent evaluation: using metrics for tool use accuracy, conversation consistency, and action success rates.


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