Leads enterprise AI platform adoption by embedding with IT teams, building agentic workflows and integrations, improving software delivery and operations, and measuring engineering efficiency. Applies AI across the SDLC, DevSecOps, observability, security, governance, and legacy modernization. Translates field learnings into reusable platform capabilities, influences senior stakeholders, mentors engineers, and serves as a technical escalation point without direct management responsibility.

Manage delivery of a portfolio of AI and data science projects from planning through implementation. Coordinate technical and non-technical teams, dependencies, requirements, budgets, timelines, and stakeholder expectations. Lead Agile ceremonies, drive accountability, translate AI capabilities into actionable requirements, and proactively identify and mitigate risks across complex, concurrent initiatives.

Lead and grow an AI Platform engineering team delivering cloud-native infrastructure for AI/ML development. Own people leadership, hiring, roadmap delivery, architecture reviews, engineering standards, stakeholder communication, and team wellbeing while partnering across AI, product, and cloud teams.