Principal Technical Program Management- AI Accelerator Software Planning

Microsoft Microsoft · Big Tech · Mountain View, CA +2 · Technical Program Management

This role is for a Principal Program Manager at Microsoft, focused on planning and executing software for an advanced AI infrastructure platform, specifically an accelerator platform. The role involves deep integration across hardware and software, including silicon, firmware, systems software, and AI infrastructure. The candidate will drive end-to-end execution, manage cross-functional programs, and ensure readiness for platform milestones and production deployment. Familiarity with AI training and inference workloads is preferred.

What you'd actually do

  1. Own and drive end-to-end software program execution for an accelerator platform, from early development through bring-up, validation, release, and production readiness
  2. Lead cross-functional planning across the full software stack, including firmware, drivers, kernel interfaces, compilers, runtime systems, distributed infrastructure, SDKs, and tools
  3. Build and maintain integrated program plans, including schedules, dependency maps, and readiness criteria across multiple engineering teams
  4. Partner with hardware, firmware, and software teams to align on requirements, milestones, and critical path dependencies
  5. Drive new platform bring-up readiness, including sequencing of software deliverables aligned with hardware milestones and validation gates

Skills

Required

  • Bachelor's Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.
  • 3+ years of experience managing cross-functional and/or cross-team projects.

Nice to have

  • 10+ years of experience in Technical Program Management, systems software, infrastructure/platform engineering, or related technical leadership roles, with a proven track record of leading large-scale, cross-functional engineering programs.
  • Deep technical expertise in GPU, accelerator, SoC, AI infrastructure, HPC, or low-level platform software stacks, including areas such as device drivers, firmware, hardware/software interfaces, compilers, runtime systems, AI/ML frameworks, distributed systems, or high-performance computing.
  • Experience driving new platform bring-up, system integration, and hardware/software co-development efforts across complex engineering environments.
  • Strong program execution skills, including managing schedules, dependencies, risks, release readiness, and coordination across hardware, software, and external partner/vendor teams.
  • Familiarity with AI training and inference workloads, performance optimization, and system-level scalability challenges.
  • Ability to engage deeply with engineering teams on architecture decisions, technical trade-offs, and complex system design challenges.
  • Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts for diverse audiences and drive alignment across organizations.

What the JD emphasized

  • deep integration across hardware and software
  • strong technical depth in GPU or accelerator software ecosystems
  • drive end-to-end execution across the software stack
  • partner effectively with engineering teams and bring structure to highly complex, cross-functional programs
  • Deep technical expertise in GPU, accelerator, SoC, AI infrastructure, HPC, or low-level platform software stacks
  • Experience driving new platform bring-up, system integration, and hardware/software co-development efforts across complex engineering environments
  • Familiarity with AI training and inference workloads, performance optimization, and system-level scalability challenges

Other signals

  • AI infrastructure platforms
  • high-performance accelerator platform
  • AI training and inference workloads