Senior Director - Agentic AI Development

HP•Houston, TX

About The Position

HP is shaping the future of AI by delivering intelligent, agentic experiences integrated into HP PCs and edge devices. This role leads the engineering organization responsible for transforming strategic AI concepts into scalable, production-ready solutions. The leader oversees roadmap execution, cross-functional development coordination, quality and release management, risk mitigation, and issue resolution to deliver AI experiences across applications, device services, AI execution layers, and supported hardware platforms. The role is based in locations considered in Houston or Austin, Texas, or Taipei City, Taiwan. The Senior Director leads feature delivery from product-owner priorities through executable engineering plans and production increments; develops agentic workflows and integrations; ensures integration with operating systems, hardware, and device management; establishes experience validation and release practices; and drives Agile execution. The role also hires and develops engineering managers and technical leaders across sites, and owns staffing, development investment, engineering effectiveness, and escalation of delivery risks. The position is full time. The listed U.S. annual pay range is $200,150 to $320,250, with additional bonus and/or equity opportunities for U.S. candidates. Pay varies by work location, job-related knowledge, skills, and experience.

Requirements

Typically 15 or more years in software, systems, or AI engineering.
At least 7 years of leadership experience, including 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, OS, or ISV partners and using AI-assisted engineering with human review and quality controls.

Responsibilities

Translate product-owner priorities into executable engineering plans and lead teams from prototypes to production increments, with clear ownership of implementation, 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, OS versions, and external components.
Build continuously with product owners and Foundation 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.