Director - AI Transformation Portfolio Manager

Vertex Inc.•Boston, MA

10d•$185,600 - $278,400•Hybrid

About The Position

Vertex’s Data, Technology and Engineering (DTE) organization is seeking a Director, AI Portfolio Management to join the Project Management and Strategic Operations (PMSO) team. PMSO is responsible for streamlining and simplifying the work of Vertex’s data and technology teams and supporting the successful deployment of new technologies across the global enterprise. This role reports to the Senior Director, Project Management and Strategic Operations and partners closely with the Chief Technology Officer (CTO) to oversee a portfolio of AI-driven initiatives supporting Vertex’s ambition of a tech-enabled workforce. The role requires leadership across portfolio planning, financial management, governance, and oversight of program, project, and change management. The portfolio is organized around AI-driven initiatives prioritized by value, achievability, and risk to business, with implementation supported through waves, sprint plans, timelines, investment planning, and executive review processes. This role will also help ensure AI-driven initiatives are delivered with appropriate oversight across responsible AI, data privacy, cybersecurity, and AI lifecycle management considerations, in alignment with enterprise governance and operational requirements.

Requirements

Advanced degree with strong experience in biotechnology in an information technology setting.
10 years of experience or the equivalent combination of education and experience.
Minimum of 5 years of experience in project, program, and/or portfolio management, with exceptional organization and planning skills.
Proven track record of managing complex information technology projects, coordinating cross-functional teams, and delivering results within defined timelines and budgets.
Strong experience managing the financial components of project, program, and portfolio delivery, including budgeting, forecasting, accruals, investment tracking, and cost-to-complete visibility.
Exceptional communication and presentation skills, including the ability to communicate technology, data, software engineering, and AI-enabled transformation concepts to both technical and non-technical audiences.
Strong leadership skills with the ability to influence and collaborate across functions and at all levels of the organization.
Clear and succinct written and verbal communication skills.
Demonstrated ability to mentor, coach, and motivate program and project managers.
Familiarity with responsible AI, data privacy, cybersecurity, and enterprise governance considerations for AI and data initiatives.
Familiarity with AI lifecycle and operational considerations, including deployment, adoption, monitoring, and support of AI-enabled capabilities.
Understanding of enterprise data and AI platforms, governed data foundations, and the operational considerations associated with scaling AI solutions in a complex environment.

Nice To Haves

Experience supporting enterprise technology deployments and operational activities in complex, cross-functional environments.
Experience working with AI-enabled initiatives involving workflow orchestration, enterprise system integration, governed data foundations, semantic layers, natural language analytics, live data, agentic solutions, and enterprise AI platforms.
Experience managing portfolios organized through wave-based prioritization and sprint-based implementation.
Familiarity with regulatory and quality-oriented AI implementations involving health authority guidance, country-specific requirements, structured data exchange, and GxP validation.
Experience working with vendor-supported or partner-enabled technology initiatives, including vendor evaluations, vendor risk considerations, and platform implementation dependencies.
Experience working with AI-enabled initiatives that require coordination across governance, compliance, privacy, cybersecurity, and enterprise platform stakeholders.
Experience supporting the operationalization of AI solutions in enterprise environments, including lifecycle, adoption, and ongoing performance considerations.

Responsibilities

Lead the portfolio management of AI-driven workforce transformation initiatives across DTE and partner functions.
Maintain portfolio roadmaps, ensuring alignment with strategic priorities, resource needs, and capacity planning.
Develop and manage governance processes to ensure alignment to business requirements, executive sponsorship, and strategic priorities.
Support prioritization, sequencing, and delivery of initiatives based on value to enterprise, total expected value, annual savings, achievability, risk to business, implementation timeline, investment need, current budget, and cost to complete.
Partner with stakeholders to oversee initiative execution through waves, sprint plans, MVP timing, and execution timelines.
Prepare materials for regular portfolio reviews and presentations to executive leadership, and help facilitate strategy and portfolio review meetings with senior leaders.
Communicate portfolio status, risks, issues, and decisions to DTE leadership and the Senior Director, Project Management and Strategic Operations.
Influence cross-functional stakeholders to support sound decision-making and proactive risk and issue mitigation across the portfolio.
Manage portfolio financials, including budget planning, forecasting, accruals, investment tracking, value realization, and cost-to-complete visibility.
Lead, coach, and support project and program managers to ensure excellence in delivery across AI and technology implementations.
Support adoption of AI-enabled capabilities and end-to-end process implementation across functions to expand workforce capacity and enable growth without proportional headcount expansion.
Coordinate across initiatives involving enterprise workflow orchestration, natural language interfaces, governed enterprise data, live data integration, and AI agents.
Partner with stakeholders to support initiatives involving governed enterprise data catalogs, semantic layers, queryable enterprise data, and enterprise AI data platforms.
Support initiatives with regulatory and compliance dimensions, including health authority guidance, country-specific requirements, structured data exchange, and GxP validation considerations where applicable.
Engage with external vendors, platform providers, and implementation partners as needed to support delivery, reduce vendor reliance where appropriate, and manage vendor-related dependencies and risks.
Support the responsible and effective deployment of AI-driven initiatives through appropriate governance, risk awareness, and cross-functional oversight.
Incorporate data privacy, data governance, regulatory compliance, and cybersecurity considerations into portfolio planning, prioritization, and execution.
Support oversight of the AI lifecycle across initiatives, including planning, deployment, adoption, monitoring, and ongoing operational considerations.
Partner with technical, business, and governance stakeholders to help establish scalable operating approaches for AI-enabled solutions across the enterprise.