Python Architect for Advanced Artificial Intelligence Solutions

2 days ago

Kota, Rajasthan, India beBeeGenerative Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Title: Python Architect for Generative AI

Experience: 8-12 Years

Job Description:

We are seeking a skilled Python architect with expertise in backend engineering and production experience in generative AI. The ideal candidate should have extensive core Python development experience, accompanied by focused engineering work in genAI and microservices.

Key Responsibilities:

  • Design and implement Python-based microservices integrating genAI capabilities.
  • Develop GenAI-powered solutions using Retrieval-Augmented Generation (RAG) pipelines and LLM orchestration engines.
  • Collaborate with DevOps engineers to enable CI/CD, monitoring, and observability for genAI pipelines.
  • Work closely 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.
  • 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 large language models (LLMs) on cloud platforms.
  • 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.

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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