Product Manager, Databricks Experimentation Platform

Key Responsibilities

• Define and own the product strategy, roadmap, and vision for Databricks Model Experimentation capabilities, ensuring alignment with CCB’s AI/ML platform goals and enterprise compliance requirements.
• Lead end-to-end product lifecycle management, including discovery, requirements definition, prioritization, and delivery of scalable, secure, and compliant AI/ML platform features.
• Drive the migration and integration of Databricks-based solutions, identifying dependencies, mitigating risks, and coordinating with cross-functional teams to ensure seamless execution.
• Collaborate with data science, engineering, architecture, and compliance teams to embed governance controls into product design and operations.
• Champion observability, monitoring, and operational resilience for AI/ML model experimentation workflows to ensure platform stability and reliability.
• Engage with internal customers and stakeholders to gather feedback, understand evolving needs, and translate them into actionable product enhancements.
• Lead vendor evaluation and selection processes related to model experimentation, ensuring alignment with strategic and compliance requirements.
• Communicate product vision, progress, and challenges transparently to senior leadership and critical partners, driving consensus and resource prioritization.
• Foster a culture of innovation, continuous improvement, and collaboration across product, engineering, and architecture teams.

• 8+ years of product management experience, including 3+ years leading product strategy and delivery for a large-scale Databricks-based AI/ML platform (e.g., model experimentation, MLflow, feature engineering, governance, and platform operations).
• Deep expertise in AI/ML platform capabilities, specifically feature stores, model experimentation, and lifecycle management.
• Strong hands-on knowledge of Databricks and its ecosystem, including experience with platform migrations and integrations.
• Proven track record of delivering enterprise-grade AI/ML solutions in highly regulated environments.
• Demonstrated ability to lead cross-functional teams in matrixed organizations, managing dependencies and mitigating risks effectively.
• Excellent communication skills with the ability to influence senior leadership and diverse stakeholders.
• Strong strategic thinking and customer-centric mindset, with a focus on scalability, security, and operational excellence.
• Experience with observability, monitoring, and governance frameworks for AI/ML workloads.

• Prior experience in financial services or similarly regulated industries.
• Knowledge of compliance frameworks related to AI/ML and data security.
• Strong understanding of market trends and emerging technologies in AI/ML infrastructure.