Principal TPM -AI Infrastructure

Responsibilities

• Drive availability and reliability of large-scale GPU fleets, identifying systemic issues and leading cross-functional recovery efforts.
• Support operational readiness and performance of distributed AI training and inference workloads across multi-region GPU clusters.
• Lead GPU fleet health reviews across current and next-generation hardware, including NVIDIA H200, B200, GB200/GB300 platforms and AMD Instinct MI300X, MI325X, MI350X, MI355X, and related platforms.
• Own end-to-end execution of critical AI Infrastructure GPU Operations programs, ensuring alignment with business priorities, customer needs, and operational risk signals.
• Coordinate cross-functional delivery across engineering, platform, operations, business operations, finance, observability, SRE, network, and senior leadership stakeholders.
• Manage deployment governance, change review, readiness tracking, stakeholder handoff, and operational execution processes.
• Establish and scale structured incident management mechanisms, improving root cause analysis, corrective and preventive actions, and follow-through on durable fixes.
• Serve as a primary escalation point between engineering and operations teams, resolving priority conflicts and accelerating issue resolution.
• Lead Change Review Board processes for high-volume change activity, minimizing change-related incidents and protecting service quality.
• Build, model, and maintain business planning inputs, financial forecasts, analytical views, and operating reports for AI Infrastructure GPU Operations programs.
• Own executive-level reporting, including monthly business reviews, weekly operational KPIs, critical project updates, risks, dependencies, decisions, and mitigation plans.
• Provide data-driven insights into infrastructure performance, operational risk, customer impact, and measurable program outcomes for senior leadership.
• Strengthen partnerships with hardware vendors, cloud platform teams, SRE, cloud engineering, network teams, and other internal stakeholders to improve issue resolution and operational efficiency.
• Translate complex technical, operational, and business situations into accurate narratives, recommendations, and action plans for senior stakeholders.
• Drive structured escalation and bug reporting mechanisms that reduce time-to-resolution for critical issues.
• Create and maintain documentation, playbooks, onboarding materials, runbooks, and repeatable processes that reduce ambiguity and improve execution quality.
• Drive practical use of AI and automation to improve operations productivity, reduce manual toil, accelerate triage, improve ticket prioritization, and strengthen repeatability across GPU operations workflows.
• Partner with observability and telemetry teams to improve infrastructure visibility, including RDMA telemetry, network fabric health, service health metrics, and operational dashboarding.
• Lead continuous improvement efforts such as validation frameworks, version set validation, link flap analysis, and long-tail performance optimization.
• Monitor and improve operational health across technologies such as RoCE, InfiniBand, and large-scale data center networks.

Qualifications

• 5+ years of experience in technical program management, program operations, business operations, data analysis, infrastructure operations, or a related discipline.
• Demonstrated ability to lead complex, cross-functional initiatives with measurable outcomes across technical, operations, business, and customer-facing stakeholders.
• Strong operational background with experience building cadences, governance mechanisms, KPI reporting, incident/change processes, risk management processes, or readiness programs.
• Strong written and verbal communication skills; comfortable synthesizing complex technical and operational information into executive updates, recommendations, and decisions.
• A high degree of organization and ability to manage multiple competing priorities independently through ambiguity.
• Experience identifying, measuring, and adjusting execution plans against key business, operational, reliability, or delivery metrics.
• Advanced Excel skills, including pivots, lookups, conditional logic, data modeling, and financial or operational analysis.
• Experience developing dashboards, automated reporting, or analytical tools that provide reliable business and operational visibility.
• Working knowledge of PowerPoint, Jira, Confluence, and related collaboration or delivery management tools.
• Preferred: Experience with cloud infrastructure, AI/ML infrastructure, GPU operations, data center deployment, capacity planning, or large-scale platform operations.
• Experience supporting large GPU fleets, distributed AI training or inference workloads, or performance-sensitive infrastructure environments.
• Experience with incident management, root cause analysis, corrective and preventive action tracking, Change Review Board processes, or high-volume change governance.
• Familiarity with observability, telemetry, RDMA, RoCE, InfiniBand, network fabric health, service health metrics, ticket/incident analytics, or operational dashboarding.
• Finance, business planning, workforce planning, or operational readiness experience in a technology organization.
• Track record of influencing senior business and technology leaders without relying on direct authority.