Python Developer

Role: Python Backend Developer Gen AI

Experience: 3-8 Years

Work Location: Chennai / Bangalore / Pune

Work Mode: Hybrid (working from client office)

Python Backend Developer

Key Responsibilities

• Design, develop, and maintain scalable, high-performance

  backend services

  using

  Python

  and related frameworks (e.g.,

  FastAPI

  ,

  Flask

  , or

  Django

  ).
• Integrate

  Gen AI

  models and APIs (such as

  OpenAI

  ,

  Azure OpenAI

  ,

  Anthropic

  ,

  Hugging Face

  , etc.) into backend systems.
• Develop APIs and microservices for AI-driven applications, ensuring robustness, security, and performance.
• Collaborate with data scientists, ML engineers, and frontend developers to deploy AI/ML models into production environments.
• Implement

  prompt engineering

  , model fine-tuning, and

  embedding-based retrieval (RAG)

  for intelligent application use cases.
• Optimize backend architecture for scalability, reliability, and low latency.
• Work with

  cloud platforms

  (AWS, Azure, or GCP) for model hosting, containerization, and deployment (Docker, Kubernetes).
• Ensure proper

  testing

  ,

  logging

  , and

  monitoring

  of backend services and APIs.
• Stay updated with the latest advancements in AI, LLMs, and backend technologies to bring innovation into project solutions.

Required Skills and Experience

• 3-8 years of experience in

  backend development

  with a strong focus on

  Python

  .
• Proficiency in one or more backend frameworks such as

  FastAPI

  ,

  Flask

  , or

  Django

  .
• Experience working with

  Generative AI

  tools, models, or APIs (e.g., OpenAI GPT, LangChain, Hugging Face Transformers).
• Hands-on experience with

  RESTful APIs

  or

  GraphQL

  service design.
• Strong understanding of

  data structures, algorithms, and system design

  .
• Familiarity with

  LLM application development

  ,

  prompt design

  ,

  RAG pipelines

  , and

  vector databases

  (like Pinecone, Weaviate, FAISS, or Milvus).
• Experience with

  CI/CD pipelines

  ,

  Git

  , and

  containerization

  (Docker/Kubernetes).
• Exposure to

  cloud deployment

  (AWS Lambda, Azure Functions, or GCP Cloud Run).