Lead Project Manager
The Lead Project Manager provides strategic leadership for the most complex enterprise programs and portfolios, driving Agile delivery at scale and championing AI-first project management practices. This role sets the vision for Agile and agentic AI adoption across the IT Project Management function, governs cross-portfolio dependencies, and mentors the full PM team. The Lead Project Manager partners with enterprise architecture, data, and AI governance teams to define and operationalize AI-enabled project delivery capabilities, ensuring alignment with organizational standards. Additionally, this role ensures strong alignment between technology investments and business strategy while advancing enterprise-wide delivery maturity.PRINCIPAL RESPONSIBILITIES AND DUTIES:Sets strategic portfolio vision, investment themes, and value delivery roadmaps in collaboration with executive leadership and enterprise stakeholders across business and IT.Accountable for portfolio-level governance, Agile program delivery, and continuous value realization across all phases of the delivery lifecycle.Develops portfolio-level strategies, executive communication frameworks, and AI-enhanced program dashboards for enterprise visibility.Provides executive-level communication of portfolio health, strategic delivery risks, and AI-driven program insights to C-suite and board stakeholders.Ensures enterprise programs deliver measurable business value through Agile delivery, continuous feedback loops, and AI-optimized resource allocation.Governs strategic vendor and partner ecosystems, negotiating Agile delivery contracts and ensuring AI-readiness across the vendor landscape.Leads enterprise resource strategy, championing self-organizing teams and optimizing talent allocation across the Agile portfolio.Architects enterprise dependency management strategies, using AI-powered tools to visualize and resolve cross-portfolio risks.Orchestrates enterprise PI Planning, portfolio Kanban, and strategic milestone management using AI-enhanced enterprise Agile platforms.Defines and monitors portfolio-level KPIs, value stream metrics, and AI-generated predictive delivery indicators.Develops and presents executive portfolio reviews, AI-powered forecasting reports, and strategic investment recommendations.Leads enterprise risk governance, leveraging AI-driven scenario modeling and predictive risk analytics to guide strategic decisionsSKILLS AND ABILITIES REQUIRED:Mastery of enterprise Agile and portfolio management platforms (e.g., Azure Dev Ops) with strategic oversight of toolchain selection and governance.Expert in executive communication platforms, AI-powered analytics suites, and enterprise collaboration ecosystems.Expert in enterprise architecture tools, value stream mapping, and AI-powered modeling platforms for strategic planning.Advanced data and analytics literacy, including experience governing AI/ML pipelines, data strategy, and analytics-driven portfolio decisions.Deep technical breadth across enterprise platforms, AI technologies, cloud ecosystems, and digital transformation tools.Ability to work both independently and in a team-oriented, collaborative environment.MINIMUM LEVEL OF PREPARATION AND TRAINING NORMALLY REQUIRED:A bachelor’s degree in computer science or business administration with an emphasis in management information systems or equivalent work experience.7+ years of progressive project management experience, including 5+ years leading enterprise Agile programs and AI-augmented delivery initiatives.PMP and SAFe Program Consultant (SPC) or SAFe Fellow certification required. Additional certifications in AI, Lean Portfolio Management, or enterprise Agile strongly preferred.Evaluates, selects, and oversees implementation of enterprise AI platforms for project portfolio management, resource optimization, and predictive delivery analytics.Leads Agile Center of Excellence initiatives, establishing training programs, certification pathways, and maturity assessments across the organization.Strategic expertise in agentic AI, including AI governance, enterprise AI platform evaluation, prompt engineering strategy, and building AI-first PM organizations.