Generative Artificial Intelligence (GenAI) Developer

5 - 8 years

0 - 1 Lacs

Posted:-1 days ago| Platform: Naukri logo

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Full Time

Job Description


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Position Overview

Generative AI Developer (5+ years)

Key Responsibilities

  • Design, build, and optimize 

    Generative AI/LLM-powered applications

    .
  • Develop and deploy 

    AI agents

    , chatbots, and automation workflows using agentic frameworks.
  • Build advanced 

    RAG (Retrieval-Augmented Generation)

     architectures for production use cases.
  • Fine-tune open-source and proprietary LLMs using frameworks such as 

    Hugging Face, LangChain, LlamaIndex

    , etc.
  • Implement and manage 

    vector databases

     (FAISS, Pinecone, Chroma, Weaviate) for embeddings and semantic search.
  • Develop secure, scalable backend APIs for GenAI solutions using 

    Python

     and relevant frameworks.
  • Integrate AI systems with enterprise apps, cloud platforms, and internal tools.
  • Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
  • Conduct model evaluations, performance tuning, and continuous monitoring.
  • Maintain best practices in 

    Responsible AI

    , data security, privacy, and compliance.

Required Skills & Qualifications

  • 5+ years of professional experience

     in AI/ML, with at least 

    23 years in Generative AI/LLM development

    .
  • Strong proficiency in 

    Python

    , including backend service development.
  • Hands-on expertise with 

    LLM frameworks

    : LangChain, LlamaIndex, Hugging Face Transformers.
  • Strong understanding and practical experience with:
    • Embeddings & vector stores
    • Prompt engineering & context management
    • Model fine-tuning (LoRA, PEFT, SFT)
    • RAG architectures
    • Agentic AI patterns
  • Experience with 

    cloud platforms

     (Azure, AWS, GCP) and containerization (Docker/K8s).
  • Solid knowledge of 

    transformer architectures, deep learning

    , and modern NLP techniques.
  • Familiarity with MLOps practices, CI/CD pipelines, and model deployment.
  • Excellent analytical, debugging, documentation, and communication skills.

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