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Job Type

Full Time

Job Description

We’re Hiring: AI Engineer – Generative AI, LLMs, Python, FastAPI

Experience:

Location:

About the Role

AI Engineer (Generative AI)

GenAI-powered solutions

You will collaborate with data scientists, ML engineers, and backend teams to turn advanced research into scalable production systems that deliver real-world impact.

What You’ll Do

  • Design and implement

    Generative AI applications

    powered by Large Language Models (LLMs) such as GPT, Claude, LLaMA, or Gemini.
  • Develop

    FastAPI-based microservices

    for AI model inference, orchestration, and integration with product backends.
  • Fine-tune and optimize pre-trained LLMs for domain-specific use cases using

    RAG, LoRA, or PEFT

    .
  • Implement pipelines for

    prompt engineering, embeddings, and context retrieval

    to enhance model accuracy and response quality.
  • Collaborate with data scientists to evaluate model outputs, refine responses, and ensure alignment with business logic.
  • Integrate external APIs (OpenAI, Anthropic, HuggingFace, Azure AI, etc.) into scalable production systems.
  • Develop secure, high-performance AI endpoints with proper monitoring, caching, and load management.
  • Research and experiment with new architectures, frameworks, and techniques to continuously improve GenAI capabilities.
  • Partner with cross-functional teams to deliver innovative AI-driven features in production environments.

What You’ll Need

  • 3–7 years of hands-on experience in

    AI/ML engineering

    or backend development with strong exposure to

    Generative AI

    .
  • Proficiency in

    Python

    ,

    FastAPI

    , and RESTful API development.
  • Solid understanding of

    LLMs

    ,

    prompt design

    ,

    vector databases

    (like Pinecone, FAISS, or Chroma), and

    retrieval pipelines

    .
  • Experience with

    HuggingFace Transformers

    ,

    LangChain

    ,

    LlamaIndex

    , or similar frameworks.
  • Working knowledge of

    model fine-tuning

    ,

    embeddings

    , and

    RAG-based systems

    .
  • Familiarity with cloud environments (AWS, GCP, or Azure) and MLOps tools for model deployment.
  • Strong problem-solving mindset with a focus on scalability, reliability, and maintainability.
  • Excellent collaboration skills and ability to work in an agile, fast-paced environment.

Nice to Have

  • Experience integrating

    OpenAI API

    ,

    Anthropic

    , or

    Vertex AI

    models.
  • Knowledge of

    Docker

    ,

    Kubernetes

    , or CI/CD for AI services.
  • Exposure to

    frontend integration

    for AI-powered user interfaces (Streamlit, React, or similar).
  • Experience working with

    RAG pipelines

    using

    FAISS

    ,

    Pinecone

    , or

    Weaviate

    .
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