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As the Director of TPM, Enterprise, you are not just managing programs; you are the architect of a new organizational capability. You will be responsible for building, scaling, and leading a world-class TPM team from the ground up. Your mission is to establish the strategic framework for how we execute enterprise-grade initiatives, ensuring data quality, operational efficiency, and the seamless integration of AI capabilities across all business units. You will act as a strategic partner to Engineering and Product leadership, transforming high-level business vision into a rigorous, scalable execution engine. This is a high-stakes leadership role requiring a blend of deep technical fluency (particularly in ML/AI lifecycles), organizational design, and the ability to influence at the highest levels of the company.
Job Responsibility
Recruit, hire, and mentor a high-performing team of Technical Program Managers
Define the team’s culture, operating model, and career development paths
Define the long-term execution strategy for Enterprise programs, ensuring alignment with company-wide OKRs and product milestones
Establish standardized processes for program delivery, risk management, and cross-functional communication that can scale with the company's growth
Serve as the primary bridge between Engineering, Product, and Executive leadership
Resolve high-level dependencies and resource conflicts across Platform, Data, and Product teams
Translate complex technical roadmaps and GenAI initiatives into clear business outcomes, risk profiles, and delivery forecasts for the C-suite and Board
Drive the adoption of enterprise-grade standards for data quality and infrastructure reliability
Ensure that 'Enterprise' isn't just a label, but a measurable standard of excellence across all BUs
Requirements
10+ years of experience in Technical Program Management or Engineering Leadership, with at least 4+ years in a people management capacity leading other TPMs or Engineers
Proven track record of building teams from scratch in high-growth, fast-paced environments (e.g., Series C through IPO or within a major tech incumbent)
Deep expertise in the AI/ML lifecycle, including LLM fine-tuning, performance evaluation, and the infrastructure requirements for deploying GenAI at scale
Expert-level Stakeholder Management: Ability to navigate complex organizational politics and drive consensus among diverse technical and non-technical leaders
Systems Thinking: The ability to look beyond individual projects to see the broader technical ecosystem and identify 'force multipliers' for the organization
Strategic Tooling Proficiency: Experience implementing enterprise-level planning and tracking frameworks (e.g., Jira Align, specialized roadmap software, or custom internal dashboards)
Nice to have
Engineering Background: A background as a Software or ML Engineer, providing the 'technical gravity' needed to earn the respect of senior architects and principals
Platform-First Mindset: Experience building and driving adoption of internal developer platforms or horizontal services used by thousands of internal stakeholders
Change Management Expertise: Proven ability to lead large-scale organizational shifts in methodology or technical architecture