Director, Technical Program Management - Software

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Director of Technical Program Management to lead strategy and implementation across complex software projects, focusing on AI/ML domains. This role involves scaling a TPM team, promoting operational efficiency, and driving delivery through agentic workflows and automation, with a focus on both Physical AI and Generative AI.

What you'd actually do

  1. Lead, mentor, and scale a high-performing TPM team; set expectations for ownership, velocity, and proactive execution.
  2. Define and lead the implementation approach across a large engineering organization spanning multiple products and platforms.
  3. Partner closely with engineering, product, and collaborators to align priorities and ensure successful delivery.
  4. Build deep domain understanding of technologies and products; influence both technical direction and business outcomes.
  5. Establish real-time, automated program visibility through dashboards powered by agentic workflows; ensure clear communication of status, risks, and dependencies.

Skills

Required

  • 12+ overall years of experience, including 8+ years in technical leadership or TPM roles.
  • Bachelor’s or higher degree in Computer Science, Engineering, or equivalent experience.
  • Verified experience in forming and advancing TPM organizations across broad, matrixed frameworks.
  • Strong understanding of software development processes and the ability to manage multiple complex workstreams simultaneously.
  • Ability to operate at both strategic and tactical levels, aligning collaborators and driving execution.
  • Demonstrated strength in risk management, problem-solving, and decision-making under ambiguity.
  • Excellent communication skills with a focus on transparency and clarity across complex organizations.
  • Experience leading Agile practices in large-scale software environments.
  • Hands-on experience with AI-powered developer tools or coding agents.

Nice to have

  • Background in AI/ML systems, deep learning, or large-scale data-driven products.
  • Familiarity with the AI model lifecycle, including training, fine-tuning, and evaluation.
  • Ability to contribute technically when needed, especially in Generative or Physical AI domains.
  • Experience transforming program management through automation or technology-enhanced workflows.
  • History of delivering large, complex programs with measurable business impact.

What the JD emphasized

  • agentic workflows
  • AI-powered developer tools or coding agents
  • AI model lifecycle, including training, fine-tuning, and evaluation
  • Generative or Physical AI domains