Director of Product Management (Internal AI Product Strategy & Ops)
New
Based in United StatesFull-TimeDirector
SalaryCompetitive executive-level compensation package including base salary, bonus, and potential equity participation.
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Job Details
- Experience
- 12+ years of experience (15+ preferred for senior director level)
- Required Skills
- Product ManagementGenerative AI
Requirements
- 12+ years of experience (15+ preferred for senior director level), including leadership of a strategic, company-wide product or internal platform initiative.
- Proven experience defining and scaling internal operating models or enterprise-wide digital/AI transformation programs.
- Strong fluency with modern AI tools, including assistants, agents, or generative AI systems, with a clear perspective on their enterprise impact.
- Demonstrated ability to work across complex organizations and align stakeholders in product, engineering, security, legal, and operations.
- Experience building or managing internal platforms such as knowledge systems, workflow automation tools, or AI-enabled productivity systems.
- Strong understanding of responsible AI, governance, and compliance considerations in enterprise environments.
- Excellent strategic thinking, communication, and leadership skills with the ability to influence at executive level.
- Background in healthcare, regulated industries, or complex enterprise environments is a strong plus.
- Ability to balance long-term vision with hands-on operational execution.
Responsibilities
- Own the end-to-end internal AI product strategy, defining what capabilities to build, scale, or retire as the organization evolves.
- Lead the design and evolution of the internal AI ecosystem, including knowledge layers, reusable skills, agents, and workflow automation systems.
- Establish governance, safety standards, and responsible AI frameworks in partnership with security, legal, and compliance stakeholders.
- Define and track success metrics tied to AI adoption, reuse, productivity impact, and transformation of day-to-day work.
- Drive enterprise-wide AI adoption strategy, ensuring successful rollout through enablement programs, champions, and leadership alignment.
- Run the operating cadence for internal AI initiatives, ensuring prioritization, execution discipline, and continuous iteration.
- Collaborate with engineering and data teams to translate strategy into scalable technical solutions and platform capabilities.
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