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Lead Architect for Scalable AI Solutions

3 weeks ago

Hubli, Karnataka, India beBeeGenerative Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Title: Python Lead/Architect – Generative AI

Experience: 8-12 Years

Job Description:

We are seeking an experienced Python Architect with a strong foundation in backend engineering and recent production experience in Generative AI.

The ideal candidate will have a solid understanding of microservices architecture, hands-on experience with GenAI tools like LangChain, LlamaIndex, Hugging Face Transformers, and a proven ability to design scalable, maintainable, and testable AI-driven applications.

Responsibilities include architecting and implementing Python-based microservices integrating GenAI capabilities, designing GenAI-powered solutions using Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration engines, developing RESTful APIs and backend services using FastAPI/Flask integrated with OpenAI/Azure OpenAI or open-source models.

Key Qualifications:

  • 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

Benefits:

This role offers the opportunity to work on cutting-edge AI projects, collaborate with ML engineers and data scientists, and lead design sessions, code reviews, and mentor junior engineers on architectural best practices.

Additionally, you will have the chance to implement agentic workflows using Semantic Kernel, LangGraph, or similar orchestration tools and ensure system reliability, scalability, and security across GenAI-enabled services.

Desirable 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