Senior AI Engineer

7 - 12 years

20 - 30 Lacs

Posted:3 hours ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

About the Role

AI Engineering Lead

This isn’t just a data science role — it’s a hands-on engineering position demanding architectural foresight, curiosity, and a constant pulse on evolving AI capabilities.

Key Responsibilities

  • Design and build AI-powered platforms

    , including multi-agent orchestration (CrewAI, AutoGen, LangGraph) and RAG pipelines (dense/sparse/hybrid search strategies).
  • Operationalize AI across use cases like 

    data harvesting, compliance validation, summarization, and knowledge retrieval

    .
  • Lead end-to-end implementation of LLM systems using 

    open-source stacks

     — LangChain, Haystack, HuggingFace, etc.
  • Develop 

    web-integrated AI applications

    , collaborating with front-end and backend teams (React, FastAPI, etc.).
  • Drive quality, scalability, and reliability in all AI product engineering efforts, ensuring robust deployment and monitoring.
  • Own 

    embedding lifecycle, prompt strategy, agent memory

    , and dynamic tool invocation techniques.
  • Collaborate cross-functionally across product, infra, data, and legal teams to ensure business-aligned engineering.
  • Stay ahead of the curve — proactively track AI tool evolution, contribute PoCs, and guide architectural decision-making.

Required Qualifications

  • 5+ years

     of total experience with 

    3+ years in LLM/AI product engineering leadership

    .
  • Strong track record of building 

    LLM-based products

    , including 

    RAG systems

    agents

    , or 

    AI assistants

    .
  • Deep understanding of 

    dense vs. sparse retrieval

    vector DB design

    chunking strategies

    , and 

    LLM cost/performance trade-offs

    .
  • Experience with frameworks like 

    CrewAI, AutoGen, LangGraph, BrowserBase, LangChain

    , etc.
  • Solid software engineering background — Python (must), FastAPI, SQL/NoSQL, data pipelines, and backend logic.
  • Familiarity with 

    web technologies

     and 

    browser automation/scraping frameworks

     (e.g., Puppeteer, Playwright).

cloud environments (AWS/GCP)

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