VP - PS Agentic AI PC Architecture & Development

HP•Palo Alto, CA

10d

About The Position

The VP, Agentic AI Systems & Solution Engineering reports to PS engineering leadership and is accountable for common Agentic AI systems architecture, engineering execution, and product delivery. The role leads a global, matrixed engineering organization from requirements and system design through development, integration, validation, production release, and sustaining. In partnership with division leaders and Product Management, this leader translates customer priorities into technical requirements, a prioritized roadmap, and executable delivery commitments. Division leaders and Product Management own customer, portfolio, product, and commercial decisions; the VP owns engineering feasibility, architecture, resources, schedule, quality, and delivery, with shared accountability for customer adoption and business impact. The role owns engineering delivery across four connected solution areas: device-aware AI execution, proximal intelligence, trusted agent execution, and agentic distribution. It is responsible for shared architecture and interfaces with HP platform, security, and product teams, and for delivering production-ready orchestration, policy, telemetry, context, coordination, trust, distribution, and runtime integration capabilities. The VP owns the integrated engineering plan from concept through production and sustaining; the Agentic Computing Foundation and its reference architecture; technical roadmaps, standards, and integration contracts; productization and release readiness; and lifecycle quality, security, privacy, reliability, manageability, telemetry, and supportability. The role leads technical engagement with external and internal partners, builds and develops the engineering organization, and manages engineering budgets and capacity. Success includes shipping committed solutions and reusable components in HP products, meeting agreed scope, schedule, quality, and cost, supporting customer adoption and business impact, and improving reuse, integration speed, and engineering productivity.

Requirements

10+ years in systems engineering spanning hardware, firmware, silicon (CPU/GPU/NPU), memory, OS/runtime, and software, with a record of shipping platform-level systems.
8+ years leading large (100+), globally distributed, matrixed engineering organizations with shared or division-funded resources.
Demonstrated end-to-end delivery of complex products from requirements and architecture through development, integration, validation, production release, and sustaining.
Evidence of predictable execution, recovery of at-risk programs, and management of engineering budgets and capacity.
Experience taking AI or Agentic AI systems from concept to production with measurable customer and revenue or margin impact in client, server, or edge deployments.
Direct experience with server, data-center, or distributed/edge infrastructure, including compute, memory, networking, and workload placement, and ability to apply that experience to client-connected solutions.
Experience building reusable platforms that scale across multiple product lines and deployment environments, with sound system-level trade-off judgment.
Senior-level co-engineering experience with platform, silicon, and software partners.
Ability to align division leaders and represent engineering at SVP/EVP level without direct authority.
Working knowledge of identity, isolation, trust, and enterprise manageability, including Zero Trust, TPM/Secure Boot, and compliance requirements across client and server/edge environments.

Nice To Haves

Practical experience with LLM inference, AI runtimes, agent frameworks, and coding in client and server environments.
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field; an advanced degree such as an MS or MBA is a plus.

Responsibilities

Own the integrated engineering plan from concept through production and sustaining, including deliverables, owners, milestones, capacity, dependencies, and release criteria.
Translate PM-aligned customer needs into functional requirements, engineering specifications, architecture, and prioritized development backlogs; agree scope and acceptance criteria with product owners and manage changes against commitments.
Run delivery cadence with engineering, program management, and validation leaders; track evidence-based progress, resolve blockers, escalate decisions, and execute recovery plans when delivery is at risk.
Lead productization through integration, hardening, and validation of agreed customer scenarios; deliver release-ready software and firmware packages, deployment and update mechanisms, validation evidence, and sustaining handoffs.
Own the common Agentic Computing Foundation, reference architecture, engineering specifications, and technical standards; deliver reusable libraries, services, SDKs, and documented interfaces.
Define the technical roadmap and integration contracts across four solution areas, combining HP-owned capabilities with OS, silicon, AI-runtime, and cross-HP platform technologies.
Make system-level trade-offs across performance, memory, power, thermals, latency, security, and cost; define and validate foreground-experience limits under realistic concurrent workloads.
Embed security, privacy, reliability, and enterprise manageability in requirements, architecture, and release gates; establish test coverage, AI evaluation, compatibility, performance, and recovery criteria with domain teams.
Own product lifecycle engineering, including defect closure, deployment and update readiness, telemetry, supportability, and use of field feedback to improve releases.
Lead technical engagement with OS/platform, silicon, ISV, AI platform/model, and enterprise partners; turn joint roadmaps into agreed interfaces, deliverables, resourcing, and integration milestones.
Resolve cross-HP and partner dependencies through clear technical ownership and interface agreements; use external engagement and technology scouting to improve the roadmap and accelerate delivery.
Build and lead the engineering organization, hire critical talent, develop leaders, manage performance, and establish ownership across architecture, development, integration, validation, and engineering program management.
Own engineering budgets and capacity plans; prioritize investment and build, reuse, and partner decisions with division leaders; improve productivity through shared platforms, automation, and AI-enabled development.
Deliver device-aware AI execution, including workload and memory governance, foreground protection, placement policies, and tested HP product and runtime integrations.
Deliver reusable context and device-coordination services and interfaces for validated, consent-aware workspace readiness and session transitions.
Integrate hardware-rooted trust, isolation, agent identity, and action policies to deliver enforceable access and action boundaries, auditability, and enterprise controls.
Deliver trusted compute discovery, device-capability and model-compatibility checks, authorized task handoff, distributed execution services, runtime APIs, and deployable packages supporting continuity, progress visibility, and return of results.