[Agentic AI] Senior Technical Program Manager – Execution Intelligence Foundation PMO

HP•Palo Alto, CA

11d

About The Position

The Commercial Systems Software Engineering organization is developing next-generation Agentic AI software platforms for intelligent, secure, and scalable AI experiences across client, edge, and cloud environments. The Senior Technical Program Manager will join the Program Management Office and drive planning, governance, execution, and cross-functional coordination for the Execution Intelligence Foundation. This foundation delivers orchestration, runtime, resource-governance, memory-management, and execution-intelligence capabilities that enable AI workloads and agents to operate efficiently across heterogeneous computing environments. The role partners with software architects, AI and systems engineers, platform teams, operating-system partners, silicon providers, and product organizations to coordinate delivery of frameworks, platform services, orchestration layers, runtime capabilities, resource-governance mechanisms, memory-management technologies, and execution-intelligence capabilities used across AI initiatives. The successful candidate brings experience managing large-scale software-platform programs and enough technical depth to engage with architects and engineering leaders on AI platforms, systems software, resource management, orchestration technologies, and platform infrastructure. Executive communication, cross-organizational leadership, and dependency management are critical. The position translates platform strategy and architecture into integrated roadmaps, milestones, program plans, and measurable outcomes; aligns architecture and engineering execution; coordinates a portfolio of execution-intelligence initiatives; manages risks, dependencies, and operational processes; and provides executive-ready reporting and governance. It bridges architecture strategy and engineering execution, helping deliver a common foundation for future Agentic AI innovation.

Requirements

Four-year or graduate degree in Computer Science, Engineering, Information Systems, Software Engineering, or a related discipline, or equivalent experience.
Typically 10+ years of experience in technical program management, software-platform delivery, infrastructure programs, systems engineering, or related disciplines.
Demonstrated experience managing complex software-platform initiatives involving multiple engineering teams and external dependencies.
Experience supporting AI platforms, distributed systems, runtime technologies, systems software, cloud-edge architectures, or platform infrastructure.
Experience partnering with software architects and engineering leaders on highly technical programs.
Experience working in highly matrixed and globally distributed organizations.
Proven experience presenting technical, operational, and strategic updates to senior leadership.
Working knowledge of AI and machine-learning technologies, AI runtimes, agentic AI concepts, and modern software-platform architectures.
Understanding of workload orchestration, runtime systems, resource governance, memory management, workload scheduling, and execution frameworks.
Familiarity with client, edge, cloud, and hybrid-computing architectures.
Understanding of platform software, APIs, middleware, runtime services, distributed systems, telemetry, observability, and software-development lifecycles.
Familiarity with heterogeneous computing involving CPU, GPU, NPU, memory, storage, networking, and cloud resources.
Ability to engage credibly with architects and engineers on workload execution, platform infrastructure, orchestration, performance, and resource management.
Ability to translate architecture decisions into executable plans, milestones, dependencies, and delivery commitments.
Proven success leading complex software-platform and infrastructure programs.
Strong expertise in roadmap management, integrated planning, governance, portfolio execution, and dependency management.
Experience managing cross-functional initiatives involving architecture, software, infrastructure, hardware, and ecosystem partners.
Ability to manage multiple concurrent workstreams while maintaining visibility into portfolio health.
Strong executive communication and storytelling skills, including experience creating executive presentations, dashboards, scorecards, status reports, and decision frameworks.
Ability to frame technical issues, risks, and tradeoffs in business terms.
Strong facilitation, negotiation, stakeholder-management, and leadership capabilities.
Ability to influence outcomes and drive accountability without direct authority.

Nice To Haves

Experience supporting AI platforms, agentic AI systems, workload orchestration platforms, runtime frameworks, or systems-software initiatives.
Experience coordinating initiatives involving Microsoft, Intel, AMD, Qualcomm, NVIDIA, or other technology ecosystem partners.
Familiarity with AI model execution, workload management, resource optimization, memory-management technologies, or platform orchestration frameworks.
Experience supporting architecture governance and platform strategy initiatives.
PMP, PgMP, PMI-ACP, SAFe, or comparable program-management certifications.

Responsibilities

Translate Execution Intelligence Foundation strategy and platform architecture into integrated roadmaps, milestones, program plans, and measurable business outcomes.
Drive execution of foundational AI platform capabilities, including orchestration services, execution frameworks, runtime systems, workload-governance technologies, memory-management capabilities, model-selection frameworks, and execution-intelligence services.
Coordinate activities across architecture, software engineering, quality engineering, DevOps, infrastructure, product management, and partner organizations.
Establish program objectives, ownership models, dependencies, readiness criteria, resource plans, and success metrics.
Ensure investments align with long-term AI platform strategy and business priorities, and drive predictable delivery of shared capabilities used by multiple teams.
Maintain alignment between technical strategy and engineering execution; coordinate architecture reviews, design reviews, dependency-management forums, execution reviews, and planning activities.
Drive resolution of conflicting priorities, overlapping functionality, architectural dependencies, and execution risks.
Promote consistent evolution of common platform services, frameworks, APIs, and runtime capabilities, and support governance that maximizes reuse, scalability, and maintainability.
Coordinate initiatives involving workload orchestration, execution policies, resource governance, memory management, runtime frameworks, model-selection strategies, and agent-execution capabilities.
Manage dependencies involving operating systems, hardware platforms, AI runtimes, silicon roadmaps, drivers, SDKs, and platform services.
Support validation, integration, deployment, and readiness activities across workstreams; align roadmap priorities and technology investments with internal and external stakeholders.
Coordinate proof-of-concept efforts, technology evaluations, and innovation initiatives for future platform evolution.
Identify and manage technical, organizational, partner, schedule, and integration risks; track dependencies across software, hardware, runtimes, AI services, platform frameworks, operating systems, and ecosystem partners.
Drive mitigation planning and issue resolution before milestones are affected; establish decision tracking, action-item management, escalation processes, and operational reviews.
Maintain visibility into program health and execution readiness.
Create executive-ready dashboards, scorecards, program reviews, architecture updates, risk assessments, and decision-support materials.
Present milestone status, technical progress, strategic risks, dependencies, recommendations, and key decisions to senior leadership.
Translate technical platform topics into business implications and investment recommendations; support governance, executive, portfolio, and architecture-leadership reviews.
Apply PMO best practices to improve predictability, accountability, transparency, and execution effectiveness.