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AI Architect – Generative AI

10 years

0 Lacs

India

Posted:1 week ago| Platform: Linkedin logo

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Skills Required

ai ml design architecture retrieval database data engineering openai model drive documentation governance development tuning tensorflow aws gcp azure kubernetes deployment tracking vision processing support communication management

Work Mode

Remote

Job Type

Contractual

Job Description

Job Title:

Experience:

Location:

Duration:

Type:

Job Summary:

AI Architect

Key Responsibilities:

  • Design, develop, and oversee scalable

    AI/ML architectures

    across cloud and hybrid environments.
  • Lead the

    implementation of Generative AI solutions

    , including LLM-based applications (e.g., GPT, LLaMA, Claude).
  • Architect and optimize

    Retrieval-Augmented Generation (RAG)

    pipelines and vector database integration.
  • Collaborate with product, data science, and engineering teams to translate business requirements into robust AI systems.
  • Evaluate and integrate

    open-source

    and commercial GenAI models (e.g., Hugging Face, OpenAI, Anthropic).
  • Establish best practices for

    model fine-tuning

    ,

    prompt engineering

    , and

    AI safety/compliance

    .
  • Drive

    PoC to production lifecycle

    for GenAI tools like chatbots, document summarizers, copilots, etc.
  • Maintain technical documentation, governance frameworks, and model performance monitoring.

Must-Have Skills:

  • 8–10 years of experience in

    AI/ML development and architecture

    .
  • Hands-on experience with

    Generative AI models

    like GPT, BERT, LLaMA, Claude, etc.
  • Deep knowledge of

    LLMs

    ,

    transformer architectures

    ,

    embedding models

    , and

    fine-tuning techniques

    .
  • Expertise in

    Python

    ,

    TensorFlow/PyTorch

    , and

    Hugging Face Transformers

    .
  • Experience with

    LangChain

    ,

    LLM orchestration

    , and

    vector DBs

    like

    Pinecone

    ,

    FAISS

    , or

    Weaviate

    .
  • Solid understanding of

    cloud services

    (AWS/GCP/Azure), Kubernetes, and scalable model deployment strategies.
  • Familiarity with

    MLOps practices

    , including CI/CD for ML, experiment tracking, and monitoring.
  • Strong knowledge of

    data privacy

    ,

    AI ethics

    , and

    responsible AI frameworks

    .

Preferred Skills:

  • Exposure to

    multi-modal models

    (vision + language).
  • Experience deploying

    enterprise GenAI use cases

    (e.g., document processing, customer support bots, knowledge assistants).
  • Contributions to open-source GenAI frameworks or communities.
  • Strong communication and stakeholder management skills.

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