Job Summary:
The GenAI Product Engineering Lead will drive the design, development, and delivery of an enterprise-grade Generative AI platform on Microsoft Azure. This role will provide technical leadership across agent-based systems, Azure AI, Power Platform, and cloud-native engineering while leading a multidisciplinary engineering team. The position will focus on building scalable, secure, intelligent, and production-ready solutions that transform business operations, with an emphasis on application engineering, innovation, and operational excellence.
Key Responsibilities:
• Lead, mentor, and grow a high-performing engineering team while fostering innovation, accountability, and continuous improvement.
• Architect, design, build, and scale enterprise-grade GenAI solutions on Microsoft Azure.
• Lead the end-to-end development of agentic GenAI applications using Azure AI, including Azure AI Foundry.
• Design and develop multi-agent systems using RAG, APIs, microservices, and frameworks such as LangChain or LangGraph.
• Drive solutions from concept through production, ensuring scalability, security, reliability, and operational excellence.
• Develop scalable workflows and intelligent business solutions using cloud-native engineering practices.
• Apply strong hands-on expertise with LLMs, AI/ML, and Python to guide technical implementation.
• Establish and maintain solid CI/CD practices across application development and platform engineering.
• Lead multidisciplinary engineering teams and manage offshore delivery teams of approximately 20 members.
• Shape technical direction, promote innovation, and ensure high-quality engineering outcomes.
Required Qualifications:
• 10+ years of experience in AI/ML engineering.
• 5-7 years of experience leading engineering teams and managing offshore delivery.
• Expertise in Azure AI, including Azure AI Foundry.
• Hands-on experience building agentic Generative AI applications end-to-end.
• Strong hands-on experience with LLMs, AI/ML, and Python.
• Proven experience designing and developing multi-agent systems.
• Strong knowledge of RAG, APIs, microservices, and agent frameworks such as LangChain or LangGraph.
• Full-stack engineering background with a strong focus on application development rather than data science.
• Strong understanding and hands-on experience with CI/CD practices.
• Demonstrated ability to build scalable workflows and take solutions from concept through production.
• Strong technical leadership, team management, mentoring, and delivery management skills.
