AI Engineer

1 day ago

Mangalore, Karnataka, India beBeeGenerative Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Python Architect for Generative AI Systems

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We are seeking a seasoned Python Architect with expertise in backend engineering and hands-on 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.

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

Additionally, the candidate will 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.

Key Responsibilities:

  • Architect and implement Python-based microservices integrating GenAI capabilities
  • Design GenAI-powered solutions using 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

Required Skills:

  • 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

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
  • Familiarity with agile development and cross-functional engineering collaboration

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