Principal AI Backend Developer

5 days ago

Gulbarga, Karnataka, India beBeeSoftware Full time ₹ 10,00,000 - ₹ 21,50,000
Senior AI Software Engineer

We are seeking a seasoned backend software engineer with a strong foundation in engineering scalable AI systems and recent experience working on Generative AI projects.

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 perfect for individuals who are passionate about architecting reliable AI solutions, writing production-grade code, and implementing DevOps practices for AI-powered microservices in enterprise environments.

Main Responsibilities:
  • Design and implement Python-based microservices integrating GenAI capabilities
  • Develop RESTful APIs and backend services using FastAPI/Flask integrated with OpenAI/Azure OpenAI or open-source models
  • Collaborate with DevOps engineers to enable CI/CD, monitoring, and observability for GenAI pipelines
  • Work 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
Key Requirements:
  • 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)
  • Familiarity with vector databases like FAISS, Pinecone, or Weaviate
  • DevOps practices: CI/CD with GitHub Actions, Docker, Kubernetes, Terraform
Preferred 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

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