The Role:

Are you a seasoned program leader who thrives at the frontier of artificial intelligence, agentic systems, and large-scale hardware innovation? We're looking for a Senior Technical Program Manager to own and drive the AI transformation strategy across our entire Hardware Engineering organization.

In this autonomous role, you will set the multi-year roadmap for how AI agents, orchestration frameworks, and intelligent systems reshape how our hardware teams design, build, validate, and ship world-class products. You will operate as a trusted thought partner to VP- and SVP-level leaders, define the strategic AI portfolio across hundreds of engineers, and personally architect the operating model that turns AI from experimentation into durable, org-wide capability. You will be expected to identify second- and third-order opportunities others miss, navigate ambiguity without a playbook, and deliver outcomes that materially change the trajectory of the business.

Key job responsibilities

Key Responsibilities:
• Set the AI Transformation Strategy - Define and own the multi-year AI roadmap for Hardware Engineering, aligning org-wide investments with business priorities and influencing executive decisions on capability bets, build-vs-buy, and platform direction.
• Partner on Architecture of Agentic Systems for Engineering Workflows - Lead the design and deployment of AI agents, multi-agent orchestration patterns, and RAG-based systems that automate and augment hardware design, validation, supply chain, and program management workflows.
• Drive Org-Wide Adoption & Change - Own the adoption strategy for AI capabilities across thousands of engineers; build the coalitions, incentives, and operating mechanisms that move AI from pilot to default practice.
• Govern a Strategic Portfolio - Establish the governance, prioritization, and resource-allocation frameworks for the full AI portfolio; chair cross-functional steering reviews and make trade-off calls that span multiple VPs.
• Partner Deeply on Technical Direction - Work shoulder-to-shoulder with SDEs and platform teams to shape model selection, evaluation frameworks, MLOps practices, and orchestration architecture; provide credible technical pushback and direction.
• Influence Without Authority at the Highest Levels - Communicate strategy, risks, and outcomes through executive narratives, OP1/OP2 documents, and quarterly business reviews; influence VP-level stakeholders and represent the org externally where appropriate.
• Build Repeatable AI Operating Models - Codify successful patterns into reusable playbooks, reference architectures, and adoption frameworks that scale beyond your immediate org.
• Define Outcome Metrics That Matter - Establish the success criteria, north-star metrics, and ROI frameworks for AI investment; tie program outcomes directly to engineering velocity, product quality, and unit economics.

A day in the life

1. Morning Portfolio Triage Reviews the AI initiative dashboard across 15+ active workstreams and reprioritizes the top 5 based on shifting business signals. Reallocates engineering bandwidth and sends a crisp update on what moved and why.

2. Trade-Off Decision Session Facilitates a working session between two teams competing for the same applied scientist. Makes the call using a structured framework - opportunity cost, time-to-impact, strategic fit - and documents the rationale in a one-pager.

3. ROI Pressure-Test Sits with data science and finance to stress-test a flagship agent system's business case. Uncovers that adoption velocity, not model accuracy, is the real value driver, and updates the funding ask accordingly.

4. SVP Business Review Presents a 6-pager to the HW SVP staff on quarterly AI portfolio impact. Defends a build-vs-buy recommendation on the agent orchestration platform and walks out with alignment on a $2M investment.

BASIC QUALIFICATIONS

- 7+ years of working directly with engineering teams experience

- 5+ years of technical product or program management experience

- 3+ years of technical program management working directly with software engineering teams experience

- Experience managing programs across cross functional teams, building processes and coordinating release schedules

- Bachelor's degree or equivalent in a related technical field

- Demonstrated experience establishing AI systems, AI agents, or agent orchestration frameworks for process automation, decision support, or engineering workflow improvement.

- Proven track record owning programs end-to-end with full autonomy - from ambiguous problem framing through funding, staffing, execution, and measured business impact.

- Hands-on familiarity with the modern AI/ML stack: LLMs, RAG architectures, vector databases, agent frameworks (e.g., LangChain, LangGraph, AutoGen, Bedrock Agents), evaluation harnesses, and MLOps tooling.

- Deep fluency with software tools, data systems, and analytical platforms (e.g., SQL, Python, Tableau/QuickSight, JIRA, Confluence) and the ability to interrogate technical implementations directly.

- Experience influencing and aligning senior leaders (Director, VP, SVP) across multiple organizations on technical strategy and investment. Exceptional written communication: experience authoring executive narratives, strategy documents, and operating-plan submissions for senior leadership.

PREFERRED QUALIFICATIONS

- Master's degree in computer science, engineering, analytics, mathematics, statistics, IT or equivalent, or Bachelor's degree in Electrical or Mechanical Engineering

- MBA, PgMP, PMP, or equivalent senior program management certification, or equivalent demonstrated leadership.

- Experience influencing and aligning senior leaders (Director, VP, SVP) across multiple organizations on technical strategy and investment. Exceptional written communication: experience authoring executive narratives, strategy documents, and operating-plan submissions for senior leadership.

- Proven track record owning programs end-to-end with full autonomy - from ambiguous problem framing through funding, staffing, execution, and measured business impact.

- Hands-on familiarity with the modern AI/ML

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Sunnyvale - 171,000.00 - 231,400.00 USD annually