AAdvanced Micro Devices, Inc logo

Advanced Micro Devices, Inc

Semiconductor Manufacturing · 51k people

Director -AI Driven Silicon Design

Posted 5 Oct

What’s this role about? The Director will lead the organizational adoption of AI-driven methodologies across x86 core development, including verification, RTL, and physical design. They are responsible for building and managing an engineering team, setting technical strategy, and aligning AI initiatives with business goals.

Fishkill, New York
On-site
Full-time
10+ years exp
Bachelor degree or Postgraduate degree

Skills required

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Company

About Advanced Micro Devices, Inc We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world. Our mission is to build great products that accelerate next-generation computing experiences – the building blocks for the data center, artificial intelligence, PCs, gaming and embedded. Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges. We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance_

Advanced Micro Devices, Inc

together we advance_

ProcessorsGraphic CardsComputer PlatformsCPUGPUAPUServer64-bitVirtualizationCloud computing
AAdvanced Micro Devices, Inc logo
10,001+ employees
Semiconductor Manufacturing
1969
Public Company
Raised $4.8B

Responsibilities

  • AMD is searching for a Director of Silicon Design to lead the organization-wide adoption of AI-driven methodologies across our x86 Core Development Organization. This role owns the technical vision and execution strategy for embedding AI/ML into engineering workflows spanning functional verification, RTL design, and physical design. You will build and lead a team of engineers and technical leaders, set the multi-year vision for AI adoption in core development, and be accountable for measurable improvements in engineering efficiency and design quality. You will engage directly with Cores engineering leadership to align investments, technical priorities, and organizational adoption, and will represent AI strategy and technical direction to executive stakeholders.
  • Own the strategy, roadmap, and organizational adoption of AI-driven methodologies across verification, RTL design, and physical design within x86 core development.
  • Build, lead, and grow a team of engineers and technical leaders driving AI adoption initiatives (e.g., predictive coverage modeling, intelligent test generation and triage, RTL code assistance, timing/congestion prediction, floorplan and place-and-route optimization).
  • Partner with Cores engineering leadership, architecture, design, verification, physical design, and internal tooling/data engineering teams to prioritize investments and align AI initiatives to business and engineering priorities.
  • Define and own organizational success metrics, including verification velocity, coverage closure, PPA (power, performance, area) targets, design-cycle schedule adherence, and defect escape rate, and communicate progress to executive stakeholders.
  • Drive evaluation and adoption decisions on emerging AI tools and platforms (open-source, EDA-vendor, and internally built), including build-versus-buy and infrastructure investment recommendations.
  • Lead organizational adoption of AI-augmented workflows, including technical enablement, training, and best-practice development.
  • Identify, escalate, and resolve cross-organizational technical challenges and barriers to successful AI adoption.
  • Manage organizational headcount planning and resource allocation for the AI engineering team.
  • Serve as the primary executive point of contact for AI adoption initiatives within core development, presenting strategy, progress, and business impact to senior and executive leadership.
  • Mentor engineers and technical leaders on applying AI/ML methods to solve complex design and development challenges.

Qualification

TechnologyEngineeringManagement & LeadershipSoftwareData & Analytics

Required

  • The ideal candidate combines proven engineering leadership with credible depth in AI/ML and a working understanding of CPU core development across verification, RTL design, and/or physical design. You can set and defend a multi-year AI adoption strategy, translate it into technical execution and measurable outcomes, and build organizational buy-in from engineers and executives alike. Broad knowledge of AI/ML technology, algorithms, and tooling, and how they map to EDA and silicon development workflows, is essential for this position.

Preferred

  • Significant experience leading engineering organizations, with a track record of driving large-scale, cross-functional technical initiatives; prior people-management experience leading engineers and technical leaders.
  • Direct experience in CPU or SoC development, including verification, RTL design, and/or physical design, sufficient to credibly set priorities and evaluate tradeoffs across these domains.
  • Demonstrated experience applying AI/ML or data science approaches (or leading teams that do) to engineering, hardware design, or EDA problems, with measurable business or engineering outcomes.
  • Ability to set and defend a multi-year technical strategy, translate it into execution plans, and adjust direction based on a changing technical and business landscape.
  • A mindset that accepts accountability for organizational outcomes, ensuring technical decisions align with business and engineering goals.
  • Superb communication skills at the executive level; experience managing organizational investments, external vendors (including EDA vendors), and complex technical initiatives.
  • Experience spanning more than one of verification, RTL design, and physical design.
  • Hands-on technical background with AI/ML tooling and frameworks sufficient to engage credibly with engineering teams on model approaches, data pipelines, and tooling architecture.
  • Experience building an organization or practice from the ground up, including hiring, defining operating processes, and establishing new organizational capabilities.
  • Familiarity with EDA tooling and vendors (e.g., Synopsys, Cadence, Siemens EDA) and how AI/ML capabilities are being integrated into commercial and open-source EDA flows.
  • BS, MS, or equivalent in Computer Engineering, Computer Science, Electrical Engineering, or a related field, with direct experience.

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