3 - 7 years

3 - 6 Lacs

Posted:5 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Job Summary:

We are seeking a

Generative AI Engineer

with deep expertise in building and deploying

enterprise-scale AI solutions

using

Azure AI services

and the latest

GenAI technologies

. This role involves designing intelligent, cloud-native applications leveraging

Large Language Models (LLMs)

,

Retrieval-Augmented Generation (RAG) pipelines

,

OCR

, and

agent-based architectures

.
The ideal candidate is highly skilled in

Azure OpenAI

,

Azure ML Studio

,

Azure Cognitive Search

, and

Azure Document Intelligence

, along with hands-on experience in modern

GenAI tooling

such as

LangChain

,

LlamaIndex

, and

Semantic Kernel

.

Key Responsibilities:

  • Design, develop, and deploy

    LLM-powered applications

    using

    Azure OpenAI

    and

    RAG pipelines

    .
  • Integrate

    Azure AI services

    (Cognitive Search, Document Intelligence, ML Studio) into intelligent enterprise solutions.
  • Develop

    agent-based GenAI systems

    and orchestrate workflows using tools like

    LangChain

    ,

    LlamaIndex

    , and

    Semantic Kernel

    .
  • Build and optimize

    data ingestion pipelines

    , including OCR-based document processing.
  • Collaborate with data scientists, architects, and business stakeholders to convert requirements into scalable solutions.
  • Ensure AI applications adhere to best practices in

    security, compliance, performance

    , and

    cost-efficiency

    .

Required Skills & Experience:

  • 3-7 years of experience in AI/ML, with a focus on

    Generative AI

    and

    cloud-based AI services

    .
  • Deep hands-on knowledge of:
  • Azure OpenAI Service

  • Azure Machine Learning Studio

  • Azure Cognitive Search

  • Azure Document Intelligence (formerly Form Recognizer)

  • Proficiency in GenAI frameworks:
  • LangChain

    ,

    LlamaIndex

    , and

    Semantic Kernel

  • Strong programming skills in

    Python

    (preferred) or

    Node.js

    , with experience in

    prompt engineering

    ,

    API development

    , and

    containerization

    .
  • Familiarity with

    LLM fine-tuning

    ,

    embedding models

    ,

    vector databases

    , and

    model deployment pipelines

    .
Experience working with

RAG architectures

and

agent-based LLM systems

.

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