Director, Product Management - Internal Product & Outcome Agents

cyberu•Dublin, CA

1d•Hybrid

About The Position

Cornerstone OnDemand is seeking a Director of Product Management to lead the execution and delivery of AI-native product and outcome agents for internal business stakeholders, with a strong focus on enabling revenue and services teams through scalable, secure, data-driven solutions. This is an internal-facing product leadership role for a hands-on operator with a strong IT, enterprise systems, and data platform background who can partner closely with BU leaders to identify use cases, translate business needs into clear priorities, and drive disciplined delivery across cross-functional teams. The role requires a leader who can work effectively across product, engineering, data, architecture, IT, security, and privacy teams to deliver outcome agents that improve productivity, workflow efficiency, and measurable business outcomes.

Requirements

10+ years of experience in a product leadership role or equivalent role within enterprise software, IT, SaaS, AI, data platform, or internal systems organizations
Strong experience in internal-facing product leadership or equivalent roles supporting business operations, revenue functions, or enterprise transformation initiatives
Strong IT and enterprise systems background, with the ability to work across technical and business teams to deliver scalable internal solutions
Proven track record leading execution and delivery of AI-native products, intelligent agents, automation solutions, or workflow tools
Demonstrated ability to work directly with internal BU leaders to identify use cases, prioritize work, and deliver measurable business outcomes
Strong experience building repeatable operating models for roadmap execution, release management, and delivery governance
Expertise working with data lake and data platform products such as Databricks, Snowflake, and similar technologies
Experience working closely with security, privacy, and compliance teams
Strong understanding of data governance, access controls, privacy requirements, and secure delivery practices across AI and data platforms
Strong collaboration skills across engineering, architecture, data engineering, IT, security, privacy, and business stakeholders
Demonstrated success leading product managers and driving accountability in complex, matrixed environments

Nice To Haves

Experience delivering internal AI-native assistants, workflow agents, productivity agents, or decision-support tools
Background supporting revenue operations, sales enablement, customer success operations, or adjacent business functions
Experience working across enterprise AI and data platforms in secure or regulated environments
Familiarity with governance frameworks related to AI, data management, privacy, and enterprise controls
Experience integrating product capabilities across internal systems, shared services, and platform teams

Responsibilities

Lead execution and delivery of AI-native product and outcome agents for internal business stakeholders, with emphasis on revenue and services teams and other cross-functional business units.
Partner directly with BU leaders to identify operational pain points, workflow gaps, and high-value use cases that can be addressed through intelligent agents and internal product capabilities.
Translate business needs into clear product requirements, delivery plans, release milestones, and measurable success criteria.
Drive cross-functional execution across product, engineering, data, architecture, IT, security, privacy, and business operations teams.
Establish strong operating cadences for planning, prioritization, release management, dependency tracking, issue escalation, and execution reporting.
Ensure solutions are delivered with strong operational rigor, scalability, reliability, and adoption across internal teams.
Partner with platform, data, and engineering teams to support outcome agent delivery across enterprise systems and shared AI/data platforms.
Work closely with security, privacy, and compliance teams to ensure solutions meet enterprise requirements for access controls, governance, data usage, and trusted AI deployment.
Collaborate with data engineering and analytics teams to support delivery across modern data environments, including data lake and warehouse platforms such as Databricks, Snowflake, and similar technologies.
Use delivery, adoption, and business-impact metrics to measure success and continuously improve execution quality and time-to-value.
Lead product managers and cross-functional partners with a strong emphasis on accountability, operational discipline, and outcome delivery.