VP - PS Agentic AI PC Architecture & Development

HP•Spring, TX

11d•$300,000 - $350,000

About The Position

The VP, Agentic AI Systems & Solution Engineering reports into 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. Working with division leaders and Product Management, this leader converts customer priorities into technical requirements, a prioritized roadmap and executable delivery commitments. Division leaders and PM 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 using shared architecture and agreed interfaces with HP platform, security and product teams: device-aware AI execution; proximal intelligence across PCs, docks, displays and collaboration workspaces; trusted agent execution; and agentic distribution of tasks across devices. Deliverables include production orchestration, policy and telemetry components; reusable context and device-coordination services; security and enterprise-control integrations; and distributed execution services, runtime integration APIs and deployable packages. The VP owns the common Agentic Computing Foundation and reference architecture, technical standards, integrated engineering plan, productization and lifecycle engineering. The role leads technical engagement with platform, silicon, software, AI and enterprise partners; builds and leads the engineering organization; and owns engineering budgets and capacity plans. Success includes shipping committed solutions and reusable components, customer adoption and business impact, validated foreground responsiveness and security, increased reuse and productivity, and meeting approved capacity and budget.

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 judgment on system-level trade-offs.
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 and manage changes against commitments.
Run a disciplined delivery cadence, track evidence-based progress, resolve blockers, escalate decisions and execute recovery plans when scope, schedule, cost or quality is at risk.
Lead productization through integration, hardening and validation of customer scenarios, delivering release-ready software and firmware, deployment and update mechanisms, validation evidence and sustaining handoffs.
Own the common Agentic Computing Foundation, reference architecture, engineering specifications and technical standards, delivering reusable libraries, services, SDKs and documented interfaces.
Define the technical roadmap and integration contracts across the four solution areas, coordinating 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 measurable foreground-experience limits.
Embed security, privacy, reliability and enterprise manageability into requirements, architecture and release gates; establish testing, AI evaluation, compatibility, performance and recovery criteria.
Own product lifecycle engineering, including defect closure, deployment and update readiness, telemetry, supportability and field feedback.
Lead technical engagement with OS/platform, silicon, ISV, AI platform/model and enterprise partners, turning joint roadmaps into interfaces, deliverables, resourcing and milestones.
Resolve cross-HP and partner dependencies through technical ownership and interface agreements; use external engagement and technology scouting to inform 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.