Technical Program Manager- AI Rack Scale Validation and Debug

Hardware FYI; Austin (TX); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

AMD benefits

Job summary

AMD Austin seeks a Technical Program Manager to lead AI infrastructure programs, guiding GPU platforms, rack-level bring-up, and cluster validation. You will coordinate hardware, firmware, networking, and validation teams to drive deployment readiness.

Strong PM skills and experience with AI-enabled automation are essential. You will interface with engineering leaders, manage risks, and drive data-driven status updates while advancing automation and AI-driven operational tools across hyperscale

Qualifications

• Experience leading hardware, systems, AI infrastructure, or datacenter programs through bring-up, validation, and deployment.
• Technical understanding of GPU-based AI systems, server platforms, rack architectures, and data center infrastructure.
• Experience with GPU cluster scale testing, system stress testing, validation, or large-scale systems validation.
• Familiarity with rack-level bring-up, power, cooling, networking, cabling, and infrastructure readiness.
• Experience coordinating cross-functional engineering teams and driving issues to closure without direct authority.
• Exposure to fleet-scale validation or deployment of AI, cloud, HPC, or hyperscale infrastructure.
• Understanding of infrastructure observability, telemetry, log analytics, failure analysis, and incident-management practices.
• Knowledge of Agentic AI, AIOps, or AI-enabled automation in engineering/workflows.

Responsibilities

• Lead end-to-end program planning and execution for GPU-based AI infrastructure including server integration, rack bring-up, and deployment readiness.
• Develop and maintain program schedules, dependency maps, risk tracking, and dashboards.
• Drive alignment across GPU, CPU, firmware, BIOS/BMC, systems, networking, and lab infrastructure.
• Coordinate multi-node and multi-rack scale testing, including test strategy and readiness gates.
• Lead incident response for validation and deployment issues with cross-functional teams.
• Establish and track operational metrics like MTTR, MTTD, MTTA, and fleet health.
• Identify opportunities to apply Agentic AI and AIOps to engineering workflows and automation.

Skills

Program management

Cross-functional leadership

Technical discussion

Data-driven updates

Automation

Agentic AI / AI-driven ops

Communication

Risk management

Leadership

Education

Bachelor’s or Master’s in Systems/EE/CS

PMP/Scrum Master or equivalent

Tools

Jira

Confluence

Excel

PowerPoint

Job description

ADVANCE YOUR CAREER. ADVANCE THE WORLD.

At AMD, we believetechnology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMDis shapingthefuture.

Whetheryou’redesigning next-gen processors, enabling AI breakthroughs, orbringing leading edge products to market, every role at AMD contributes to something bigger— technologythat moves the world forward.Join us and, together, we’ll advance your career.

THE ROLE

We are seeking a Technical Program Manager to lead highly visible AI infrastructure programs focused on GPU platforms, rack-level solutions, and AI cluster validation. In this role, you will work across hardware, firmware, networking, systems, and validation teams to drive AI platforms from early system integration and bring-up through rack and cluster-scale readiness.

You will have the opportunity to work on complex AI infrastructure challenges spanning GPU and server integration, rack bring-up, scale testing, system debug, failure analysis, and deployment readiness. You will partner closely with engineering teams and senior leaders to turn complex technical dependencies into clear execution plans and help deliver reliable, scalable AI solutions for hyperscale and enterprise environments.

This is an opportunity to operate at the center of next-generation AI infrastructure development while helping teams improve how systems are validated, debugged, and deployed at scale.

THE PERSON

You are a hands-on, technically curious program leader who thrives in complex, fast-moving engineering environments. You are comfortable diving into technical discussions while also maintaining a clear view of program priorities, risks, dependencies, and business outcomes.

You bring urgency, ownership, and structure to ambiguous problems and are skilled at bringing cross-functional teams together to drive decisions and execution. You can communicate effectively with engineers working through detailed system issues as well as senior leaders who need concise, data-driven program updates. You are also excited about finding new ways to improve engineering workflows through automation, Agentic AI, and AI-driven operational tools.

KEY RESPONSIBILITIES

• Lead end-to-end program planning and execution for GPU-based AI infrastructure, including server integration, rack bring-up, cluster-scale validation, and deployment readiness.
• Develop and maintain program schedules, dependency maps, resource forecasts, risk and issue tracking, readiness criteria, and program dashboards.
• Drive alignment across GPU, CPU, firmware, BIOS/BMC, systems, networking, lab infrastructure, validation, and other engineering teams.
• Coordinate multi-node and multi-rack scale testing, including test strategy, scheduling, coverage tracking, and readiness gates.
• Drive rack-level solution execution across compute trays, switch trays, cabling, power, cooling, networking, and management infrastructure.
• Establish clear entry and exit criteria for bring-up, EVT, DVT, scale validation, and deployment phases.
• Lead coordination of platform and rack-level debug activities, helping teams rapidly triage issues, identify root causes, establish ownership, and drive issues to closure.
• Track high-impact GPU, HSIO, firmware, rack, networking, and system failures through resolution.
• Lead incident response for critical validation and deployment issues, including cross-functional debug efforts, escalation management, and executive communications.
• Establish and track operational metrics such as Mean Time to Detect (MTTD), Mean Time to Mitigate (MTTM), Mean Time to Resolution (MTTR), incident recurrence, and fleet health.
• Drive post-incident reviews, root-cause analysis, corrective actions, and preventive measures to improve system reliability and deployment readiness.
• Identify opportunities to apply Agentic AI and AIOps to engineering workflows, including automated triage, log analysis, root-cause identification, knowledge retrieval, test orchestration, and incident management.
• Partner with data and engineering teams to integrate AI-powered operational tools and establish measurable success metrics for automation initiatives.
• Provide clear, data-driven program updates to engineering teams and senior leadership while proactively escalating risks, dependencies, and critical tradeoffs.

PREFERRED EXPERIENCE

• Experience leading complex hardware, systems, AI infrastructure, or datacenter programs across bring-up, validation, and deployment.
• Technical understanding of GPU-based AI systems, server platforms, rack architectures, and datacenter infrastructure.
• Experience with GPU cluster scale testing, system stress testing, performance validation, or large-scale systems validation.
• Familiarity with rack-level bring-up and system dependencies including power, cooling, networking, cabling, and infrastructure readiness.
• Experience working through hardware and firmware debug cycles in pre-production, validation, deployment, or customer-facing environments.
• Experience coordinating cross-functional engineering teams and driving technical issues to closure without direct authority.
• Experience with fleet-scale validation or deployment of AI, cloud, HPC, or hyperscale infrastructure.
• Understanding of infrastructure observability, telemetry, log analytics, failure analysis, and incident-management practices.
• Familiarity with Agentic AI, AIOps, or AI-enabled automation for engineering, validation, debug, or operational workflows.
• Strong program management skills, including schedule management, dependency tracking, risk management, executive reporting, and cross-functional coordination.
• Experience with tools such as Jira, Confluence, dashboards, Excel, and PowerPoint.
• Strong written and verbal communication skills, including the ability to translate complex engineering issues into clear program status, risks, and business impact.

ACADEMIC CREDENTIALS

• Bachelor’s or master’s degree in Systems Engineering, Electrical Engineering, Computer Science, or a related engineering discipline is preferred.
• PMP, Scrum Master, or equivalent program management training or certification is desired.

LOCATION: Austin, TX

This role is not eligible for visa sponsorship.

#LI-CS1

Benefits offered are described:

AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.