• Lead, coach, and develop a team of platform and AI engineers, fostering a culture of technical excellence, ownership, and continuous improvement. • Provide hands-on technical leadership and architectural guidance for GenAI platform services, including LLM orchestration, prompt management, vector search, embeddings, and model integration. • Define and evolve the GenAI platform roadmap to support enterprise use cases, balancing speed of innovation with scalability, security, and cost efficiency. • Drive adoption of cloud-native and Azure-based architectures, including containerization, Kubernetes, CI/CD, infrastructure-as-code, and observability. • Establish and mature LLMOps/MLOps practices, including model lifecycle management, monitoring, evaluation, versioning, and responsible AI controls. • Partner with data science, application engineering, security, legal, and compliance teams to ensure safe, ethical, and compliant use of Generative AI technologies. • Enable self-service capabilities and reusable platform components that empower application teams to rapidly build and deploy GenAI-powered solutions. • Ensure high-quality delivery through Agile best practices, clear engineering standards, and data-driven decision-making. • Communicate technical strategy, tradeoffs, and outcomes effectively to both technical and non-technical stakeholders.