Amazon Lab126 is an inventive research and development company that designs and engineers high-profile devices like the Kindle family of products. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc. Since then, we have worked to produce best-selling tablets with breakthrough hardware technology as well as e-readers that have revolutionized reading. What will you help us create?
Work hard. Have fun. Make history
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.
