Define and own the product strategy, roadmap, and vision for Databricks Model Experimentation capabilities, ensuring alignment with CCBβs 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.
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Required Qualifications and Skills
8+ yearsΒ of product management experience, includingΒ 3+ yearsΒ leading product strategy and delivery for aΒ large-scale Databricks-based AI/ML platformΒ (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.
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Preferred Qualifications
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.