Generative AI Engineer

19 hours ago

Bengaluru, Karnataka, India MASSIVUE Full time ₹ 8,00,000 - ₹ 24,00,000 per year

Job Title: Generative AI Engineer

Experience: 5 – 7 Years

Location: Delhi / Gurugram / Bangalore / Pune / Hyderabad

Notice Period: Immediate to 15 Days

About the Role:

We are looking for an experienced
Generative AI Engineer
to design, develop, and deploy AI solutions leveraging large language models (LLMs), transformers, and modern GenAI frameworks. The ideal candidate will have strong Python skills, deep understanding of AI/ML, and hands-on experience building production-grade GenAI applications.

Key Responsibilities:

  • Design and implement end-to-end
    Generative AI solutions
    using LLMs (GPT, LLaMA, Claude, etc.).
  • Build, fine-tune, and optimize
    transformer-based models
    for specific business use cases.
  • Develop
    prompt engineering
    strategies to improve model accuracy and response quality.
  • Integrate LLMs into applications using frameworks like
    LangChain, Hugging Face, LlamaIndex
    etc.
  • Work on
    retrieval-augmented generation (RAG)
    pipelines and vector databases (Pinecone, Chroma, FAISS).
  • Deploy GenAI solutions on cloud platforms (AWS, Azure, GCP) using containerization and CI/CD pipelines.
  • Collaborate with data scientists, backend engineers, and product teams to deliver scalable AI-powered products.
  • Monitor, evaluate, and continuously improve model performance and reliability.

Required Skills & Experience:

  • 5–7 years
    of software engineering / AI experience with at least
    2+ years in Generative AI / LLM projects
    .
  • Strong programming skills in
    Python
    and experience with ML/AI libraries (
    PyTorch, TensorFlow, Transformers
    ).
  • Expertise in
    LLMs, NLP, prompt engineering, fine-tuning
    , and model deployment.
  • Hands-on experience with
    LangChain, Hugging Face, LlamaIndex
    , and vector databases.
  • Knowledge of
    RAG pipelines, embeddings, and semantic search
    .
  • Strong understanding of
    API integration, microservices, and cloud platforms (AWS/Azure/GCP)
    .
  • Familiarity with
    MLOps tools
    (MLflow, Kubeflow, Docker, Kubernetes) is a plus.

Good to Have:

  • Experience with
    multi-modal AI
    (text, image, speech).
  • Understanding of
    model evaluation metrics
    and bias mitigation techniques.
  • Contributions to open-source GenAI projects or custom LLM training experience.

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