[Agentic AI] Senior Technical Program Manager – Edge AI Platform & Systems Software PMO

HP•Palo Alto, CA

About The Position

The Commercial Systems Software Engineering organization is developing next-generation AI software platforms for intelligent, secure, and scalable experiences across client and edge computing environments. The Senior Technical Program Manager will join the Program Management Office and drive strategy, planning, governance, risk management, and execution across complex AI and systems software programs. The role partners with software architects, engineering leaders, product teams, business units, and external technology partners to align technical roadmaps and deliver integrated platform capabilities. The position requires prior knowledge of AI and machine learning technologies for client and edge devices, experience managing large, complex, cross-organizational technology programs, and executive reporting and presentation skills. The successful candidate translates technical progress, risks, dependencies, and decisions into clear, actionable communications for senior leadership. This role drives strategic Edge AI software platform initiatives spanning multiple engineering organizations, business units, and external partners. It connects strategy, architecture, planning, and delivery, while providing leadership with visibility and decision support to deliver AI capabilities predictably and at scale. Programs may span AI software, systems architecture, client and edge computing, cloud integration, and ecosystem partnerships.

Requirements

Four-year or graduate degree in Computer Science, Engineering, Information Systems, Business Management, or a related discipline, or equivalent experience.
Typically 10 or more years of experience in technical program management, engineering program management, platform delivery, or a related field.
Demonstrated experience managing complex, multi-year software or platform programs involving multiple engineering teams, organizations, products, and external dependencies.
Prior experience managing AI, Edge AI, machine learning, platform software, cloud-edge, operating system, or systems software programs.
Experience partnering with software architects and senior engineers on technically complex initiatives.
Experience working in highly matrixed and globally distributed organizations.
Demonstrated experience presenting program status, risks, decisions, and recommendations to senior executives.
Working knowledge of AI and machine learning concepts, including model inference, AI runtimes, model optimization, and deployment.
Understanding of Edge AI and the performance, resource, power, security, and connectivity constraints associated with running AI workloads on client and edge devices.
Familiarity with heterogeneous computing across CPU, GPU, NPU, memory, storage, and cloud resources.
Understanding of agentic AI concepts, workload orchestration, local and hybrid AI execution, telemetry, and performance measurement.
Familiarity with software architecture, platform integration, APIs, security, quality, and modern software development lifecycles.
Ability to participate credibly in technical discussions and convert architectural decisions into plans, milestones, dependencies, and execution actions.
Proven success delivering complex technology programs involving interdependent software and hardware components.
Strong experience in integrated planning, roadmap management, milestone tracking, and delivery governance.
Expertise in managing risks, issues, decisions, assumptions, and cross-organizational dependencies.
Ability to manage multiple workstreams while maintaining an accurate view of overall program health.
Demonstrated ability to bring clarity and structure to ambiguous and rapidly evolving programs.
Proven experience creating executive-level presentations, dashboards, program reviews, and decision documents.
Ability to present confidently and concisely to senior leadership.
Strong ability to frame complex issues as clear options, tradeoffs, recommendations, and decisions.
Ability to communicate technical complexity in terms of customer impact, business outcomes, investment considerations, and delivery risk.
Strong written communication, presentation, facilitation, negotiation, and stakeholder-management skills.
Ability to influence outcomes and drive accountability without direct authority.

Nice To Haves

Experience delivering AI or systems software for PCs, edge devices, embedded systems, or enterprise endpoints.
Experience with AI inference frameworks, model runtimes, telemetry systems, performance engineering, or device-management technologies.
Experience coordinating programs with silicon providers, operating-system vendors, cloud providers, or independent software vendors.
Experience supporting architecture governance and alignment across multiple business units.
PMP, PgMP, PMI-ACP, SAFe, or comparable program-management certification.

Responsibilities

Translate business and technology strategy into integrated program plans, roadmaps, milestones, and measurable outcomes.
Drive complex Edge AI and systems software programs from strategy and architecture through development, validation, and delivery.
Coordinate execution across architecture, software engineering, product management, quality, security, and business teams.
Work with architects and engineering leaders to align delivery plans with the target architecture and technical roadmap.
Establish deliverables, ownership, dependencies, readiness criteria, and success measures.
Drive alignment across business units toward a common architecture, roadmap, and delivery plan.
Identify conflicting priorities, overlapping work, unclear ownership, and schedule misalignment, and facilitate timely resolution.
Manage technical, resource, schedule, organizational, and partner-related risks and dependencies.
Surface issues early, develop mitigation plans, frame tradeoffs, and drive decisions through closure.
Establish execution rhythms, including program reviews, technical checkpoints, decision forums, and leadership updates.
Create executive-ready dashboards, scorecards, status reports, presentations, and decision materials.
Present program status, accomplishments, risks, dependencies, options, and recommendations to senior leadership.
Translate complex technical information into clear business implications, customer outcomes, and decision points.
Coordinate commitments and dependencies with external technology and ecosystem partners.
Apply PMO frameworks, governance practices, and reporting standards to improve execution predictability.
Promote accountability, transparency, collaboration, and continuous improvement across participating teams.