Director - Agentic AI Development

HP•Spring, TX

1d•$182,750 - $278,450

About The Position

HP is seeking a leader to direct the engineering organization that turns strategic and prioritized agentic AI experiences into integrated, production-ready features for HP PCs and edge devices. The role owns roadmap execution, development coordination, quality, release management, risk mitigation, issue escalation, and delivery across applications, device services, AI execution layers, and supported hardware platforms. The Director will lead engineering teams from prototypes through production increments; build agentic capabilities such as context-aware workflows, tool integrations, planning and execution logic, and local or hybrid inference; and ensure features integrate with operating-system services, hardware, and device management. The role establishes scenario-based evaluations and automated tests on representative hardware, and manages integration readiness, release evidence, rollout sequencing, rollback plans, and field issue resolution. The Director will work continuously with Product Owners and Foundation teams around shared backlogs and sprint goals, surface and address delivery risks, and use demonstrations and adoption evidence to improve execution. The role also hires and develops engineering managers and technical leaders across sites and owns staffing, development investment, engineering effectiveness, and executive escalation of delivery risks. The listed locations are Houston and Austin, Texas, and Taipei City, Taiwan.

Requirements

Typically 15 or more years of experience in software, systems, or AI engineering.
At least 7 years of leadership experience, including experience managing managers across multiple engineering teams.
Demonstrated delivery of shipped AI-enabled PCs, connected devices, or embedded products, with accountability for device integration, release quality, and post-launch reliability.
Practical engineering depth in agentic or generative AI applications, including tool calling, context handling, local or hybrid inference, and systematic evaluation of AI behavior.
Experience integrating native applications or services with operating-system and device interfaces, and diagnosing performance or reliability issues across software and hardware boundaries.
Experience with automated integration, hardware-based validation, staged releases, rollback, and field telemetry; ability to balance task quality with latency, memory, power, and privacy.
Strong global people and delivery leadership, technical judgment, and executive communication.
Degree in computer science, electrical or computer engineering, or a related field, or equivalent relevant experience.

Nice To Haves

Experience developing for Windows PCs, multiple processor architectures, or device portfolios with differing CPU, GPU, and NPU capabilities.
Background in multimodal agents, cross-device workflows, enterprise endpoint software, or production integration of third-party AI capabilities.
Experience working with OEM, ODM, silicon, operating-system, or ISV partners.
Experience using AI-assisted engineering with human review and quality controls.

Responsibilities

Translate Product Owner priorities into executable engineering plans and lead squads from prototypes to production increments, with clear implementation ownership, dependencies, and delivery commitments.
Build context-aware agentic workflows, tool integrations, planning and execution logic, and local or hybrid inference; design for bounded actions, human oversight, interruption, and recovery.
Integrate features with Foundation APIs, operating-system services, hardware capabilities, and device management, addressing startup, sleep and resume, offline operation, updates, and failure conditions on target devices.
Establish scenario-based agent evaluations and automated tests on representative hardware; measure task success, latency, memory, battery impact, security behavior, and cross-device continuity.
Own integration readiness, release evidence, rollout sequencing, rollback plans, and field issue resolution; coordinate compatibility across device variants, operating-system versions, and external components.
Build continuously with Product Owners and Foundation teams around a shared backlog and sprint goal; surface risks early, drive recovery actions, and use demonstrations and adoption evidence to improve delivery.
Hire and develop engineering managers and technical leaders across sites; own staffing, development investment, engineering effectiveness, and executive escalation of delivery risks.
Establish success-measure baselines and agree targets with leadership, Divisions, and partner teams during initial planning.