Python Expert

3 days ago

Mumbai, Maharashtra, India beBeeGenerative Full time US$ 20,00,000 - US$ 24,00,000

Job Title: Python Lead/Architect – Generative AI

We are looking for a hands-on Python Architect with a strong foundation in backend engineering and recent production experience in Generative AI.

The ideal candidate will have 8-10 years of core Python development experience, along with 2-2.5 years of focused engineering work in GenAI and microservices.

This role is ideal for individuals who are passionate about architecting scalable AI solutions, writing production-grade code, and enabling DevOps practices for AI-powered microservices in enterprise environments.

  • Primary Responsibilities:
  • Architect and implement Python-based microservices integrating GenAI capabilities
  • Design GenAI-powered solutions using Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration engines
  • Develop RESTful APIs and backend services using FastAPI/Flask integrated with OpenAI/Azure OpenAI or open-source models
  • Work with DevOps engineers to enable CI/CD, monitoring, and observability for GenAI pipelines
  • Collaborate with ML engineers and data scientists to optimize GenAI system performance and scalability
  • Lead design sessions, code reviews, and mentor junior engineers on architectural best practices
  • Implement agentic workflows using Semantic Kernel, LangGraph, or similar orchestration tools
  • Ensure system reliability, scalability, and security across GenAI-enabled services

Core Skills Required:

  • Expert-level Python development skills including experience with FastAPI, Flask, asyncio
  • Strong understanding of microservices architecture and distributed systems
  • Hands-on experience with GenAI tools: LangChain, LlamaIndex, Hugging Face Transformers
  • Practical knowledge of deploying LLMs on cloud platforms (Azure OpenAI preferred)
  • Experience with REST API design and integration with external AI services
  • Familiarity with vector databases like FAISS, Pinecone, or Weaviate
  • DevOps practices: CI/CD with GitHub Actions, Docker, Kubernetes, Terraform
  • Proven ability to design scalable, maintainable, and testable AI-driven applications

Secondary / Nice-to-Have Skills:

  • Experience with agentic orchestration systems such as Autogen, Semantic Kernel, LangGraph
  • Exposure to fine-tuning open-source LLMs and deployment in containerized environments
  • Understanding of AI observability, performance tuning, and system logging
  • Background in MLOps and collaboration with Data Science/ML teams
  • Familiarity with agile development and cross-functional engineering collaboration

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