Principal Tech Infra PM for ML Capacity Delivery

Amazon Web Services (AWS); Herndon (VA); On-site; USD 177,000 - 239,000; Full time

Benefits offered by this job

Health insurance

RSUs and equity components

401(k) matching

Paid time off and family leave

Career growth and mentorship

Job summary

Amazon Data Services, Inc. seeks a Principal Technical Infrastructure Program Manager to define the technical vision, roadmap, and strategy for ML capacity delivery platforms at global scale.

You will lead cross‑functional teams across systems engineering, software, BIE, and operations to translate complex requirements into scalable tooling. You will drive architecture for automated capacity workflows, enable observability, and set engineering standards while partnering with internal platform

Qualifications

• 10+ years of program management, tech program management, or related experience.
• 10+ years of working directly with engineering teams experience.
• Experience defining roadmap strategy and prioritizing deliverables for your team products.
• 4+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience.
• Bachelor's degree or above in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline.

Responsibilities

• Own the technical vision and multi-year roadmap (1–3 years) for ML Capacity Delivery systems and tools, aligning investments to business priorities and capacity delivery goals across core and Gen AI platforms.
• Drive cross-functional alignment across systems engineering, software development, BIE, operations, and planning teams to define requirements, prioritize capabilities, and deliver integrated tooling solutions.
• Architect and deliver scalable platforms that automate and optimize capacity delivery workflows; including demand planning, build tracking, supply chain visibility, and operational reporting.
• Serve as the technical authority for systems and tools within MLZ, influencing Director/VP-level leadership on investment decisions, build-vs-buy trade-offs, and platform strategy through data-driven business cases.
• Identify and eliminate operational friction by mapping end-to-end workflows, quantifying inefficiencies, and delivering automation that reduces manual effort and accelerates delivery velocity.
• Establish engineering excellence; define standards for system reliability, data quality, observability, and documentation that enable teams to build and operate with confidence at scale.
• Force-multiply across the organization by creating reusable frameworks, mechanisms, and best practices that elevate the effectiveness of multiple teams and programs simultaneously.
• Drive clarity in highly ambiguous environments where the business strategy, architectural approach, and problem definition may not yet exist. While decomposing complex challenges into actionable execution plans.
• Build and maintain strategic partnerships with internal platform teams, data engineering organizations, and tooling providers to ensure MLZ systems integrate seamlessly with the broader AWS infrastructure ecosystem.
• Establish metrics, dashboards, and reporting mechanisms to provide stakeholders and senior leadership clear insight into platform health, delivery timelines, adoption, and business impact.

Skills

Program management

Engineering collaboration

Roadmap strategy

Cross-functional leadership

AI/ML infrastructure

Leadership communication

Automation/Monitoring

GPU/accelerator deployments

Data center experience

Strategic partnering

Education

Bachelor's degree or above in CS/CE/Info Management

Job description

Amazon Data Services, Inc. seeks a Principal Technical Infrastructure Program Manager to define the technical vision, roadmap, and strategy for ML capacity delivery platforms at global scale.

You will lead cross‑functional teams across systems engineering, software, BIE, and operations to translate complex requirements into scalable tooling. You will drive architecture for automated capacity workflows, enable observability, and set engineering standards while partnering with internal platform