Enterprise AI Architect

6 days ago

Noida, Uttar Pradesh, India beBeeTechnologist Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Opportunity

Description: We are seeking a visionary Python architect with a deep foundation in enterprise backend engineering and extensive experience in Generative AI at scale.

Key Responsibilities:

  • Lead Architectural Design: Define and own the architectural roadmap for enterprise-grade Python microservices and GenAI platforms.
  • System Design: Develop end-to-end GenAI-powered solutions, focusing on Retrieval-Augmented Generation (RAG) pipelines and sophisticated LLM orchestration engines.
  • Technical Governance: Establish technical standards, best practices, and governance for RESTful API design and backend services using FastAPI/Flask, ensuring seamless integration with OpenAI/Azure OpenAI or open-source models.
  • DevOps & MLOps Strategy: Collaborate with DevOps and MLOps teams to define and enable a cohesive CI/CD, monitoring, and observability strategy for all GenAI pipelines and services.
  • Strategic Collaboration: Partner with ML engineers and data scientists to optimize system-level performance and scalability, ensuring the long-term viability of AI solutions.
  • Team Guidance: Lead by example, conducting high-level design reviews, setting architectural direction, and mentoring multiple engineering teams on technical excellence.
  • Advanced Orchestration: Drive the adoption and implementation of advanced agentic workflows using frameworks like Semantic Kernel, LangGraph, or other cutting-edge orchestration tools.
  • Platform Security: Champion and ensure system reliability, security, and scalability across the entire portfolio of GenAI-enabled services.

Core Skills and Qualifications:

  • Python Expertise: Proficiency in Python development, with deep experience in designing and building with frameworks like FastAPI, Flask, and asyncio.
  • Architectural Leadership: Proven track record of architecting and delivering complex, distributed microservices and systems at enterprise scale.
  • GenAI Knowledge: In-depth understanding of GenAI tools, including LangChain, LlamaIndex, Hugging Face Transformers, and their production deployment.
  • Cloud Platform Management: Extensive experience deploying and managing LLMs on cloud platforms, with a strong preference for Azure OpenAI.
  • API & Data Design: Expertise in REST API design, system integration, and advanced use of vector databases like FAISS, Pinecone, or Weaviate.
  • DevOps Strategy: Strategic understanding and practical experience with DevOps practices, including CI/CD with GitHub Actions, Docker, Kubernetes, and Terraform.
  • Technical Leadership: Demonstrated ability to lead complex technical initiatives and define architectural direction for a group of engineers.

Secondary / Nice-to-Have Skills:

  • Agentic Orchestration: Experience with multi-agent systems and advanced orchestration tools like Autogen or LangGraph.
  • LLM Lifecycle Management: Background in fine-tuning, serving, and managing the lifecycle of open-source LLMs in a production environment.
  • Observability & Security: Deep understanding of AI observability, security, and performance tuning at a systemic level.
  • MLOps & Data Science: A background in MLOps and a proven ability to collaborate effectively with Data Science and ML teams to deliver business value

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