Top Program Manager Jobs

Lead complex technical programs for NVIDIA’s autonomous vehicle platform, driving software and hardware technologies from bring-up through production. Manage roadmaps, releases, schedules, risks, dependencies, quality, and cross-functional engineering teams across software, hardware, vehicle, systems, and validation. Improve development processes, coordinate automotive software releases, and communicate program status and decisions. The role requires strong technical knowledge, leadership, and experience delivering commercial software products in fast-paced environments.

Leads complex CPU silicon and platform programs from development through customer readiness. Coordinates architecture, engineering, firmware, validation, performance, operations, product, and customer-facing teams; manages dependencies, risks, decisions, requirements, schedules, and readiness criteria. Translates technical inputs into program plans and executive updates, maintains traceability for customer commitments, and improves execution through dashboards, automation, and operating mechanisms.

Lead end-to-end technical program management for silicon, board, and system development projects from product definition through mass production. Coordinate engineering, design, operations, and marketing teams; manage requirements, schedules, milestones, risks, budgets, and feature tradeoffs; provide semiconductor expertise; and communicate progress to senior stakeholders while improving program execution processes.

Lead large-scale cloud infrastructure programs for NVIDIA DGX Cloud, partnering with cloud service providers and internal engineering teams to bring up global AI capacity. Define technical requirements, roadmaps, milestones, KPIs, and operational processes across compute, storage, networking, and GPU infrastructure. Manage capacity operations, risks, partner alignment, infrastructure deployments, compliance, security, and observability while driving continuous improvement and executive communication.

Lead cross-functional AI safety programs for Nemotron LLMs, including agentic-safety evaluations, red teaming, model release readiness, risk governance, mitigation tracking, and executive reporting. Translate evaluation findings into prioritized mitigation plans, establish safety benchmarks and release gates, manage dependencies and escalations, and communicate residual risks and release recommendations to leadership.

Leads complex autonomous vehicle platform programs from embedded bring-up through production release. Coordinates software, hardware, validation, and systems engineering teams; drives roadmaps, schedules, milestones, risk resolution, cross-functional dependencies, and automotive software releases. Requires deep embedded systems and platform software expertise, strong technical leadership, and experience delivering commercial software products. Familiarity with autonomous vehicles, automotive standards, distributed global teams, Agile, Scrum, Jira, and PMP practices is advantageous.

Leads complex DGX Cloud production engineering programs, coordinating engineering, operations, reliability, and partner teams. Defines program structures, milestones, governance, readiness reviews, risk management, and success criteria. Improves operational rigor, delivery predictability, automation, reliability, and production readiness while communicating status and recommendations to technical and executive stakeholders.

Leads complex technical programs for DGX Cloud infrastructure operations, service health, reliability, operational readiness, and platform availability. Coordinates engineering, operations, and reliability teams; manages plans, dependencies, risks, metrics, issue reviews, and maintenance readiness. Translates telemetry and incident trends into prioritized actions and communicates progress, tradeoffs, and recommendations to technical and executive stakeholders.

Lead strategy and execution for NVIDIA’s DGX Cloud platform infrastructure. The role develops roadmaps, execution plans, operating models, dependency maps, and technical tradeoff recommendations across infrastructure, platform software, and engineering teams. The TPM will align stakeholders, influence decisions without direct authority, connect long-term platform goals to delivery, and improve planning, governance, and execution processes.

Lead technical strategy, architecture, and multi-year roadmaps for networking supporting hyperscale AI training and inference infrastructure. Evaluate InfiniBand, RDMA, Ethernet, switches, optics, and interconnect technologies; translate AI workload needs into system requirements; influence suppliers and cross-functional stakeholders; and drive initiatives from proof of concept through qualification, production deployment, and lifecycle improvement. Establish performance and reliability metrics while resolving technical, operational, supply, and execution risks.

Leads capture, planning, execution, and closeout of $5M–$25M radiation-hardened microelectronics development programs. Manages cost, schedule, technical performance, earned value, risks, opportunities, proposals, customer relationships, and cross-functional teams. Coordinates with engineering, supply chain, operations, finance, customers, and suppliers while supporting business development and government program capture. The hybrid role requires 80%+ on-site presence due to classified work.

Leads integrated execution of a U.S. Air Force aircraft development program from concept development through integration, flight testing, demonstration, and production readiness. Coordinates engineering, manufacturing, supply chain, government stakeholders, and industry partners while managing schedules, budgets, risks, technical dependencies, customer commitments, affordability, and production transition. Provides executive visibility and drives resolution of critical-path issues across aircraft, propulsion, avionics, autonomy, mission systems, and ground systems.

Leads new product introductions and full product lifecycle activities, coordinating Engineering, Manufacturing, Quality Assurance, Procurement, and Operations. Manages complex NPI projects, tooling, budgets, forecasts, cost targets, sourcing strategies, BOM accuracy, manufacturing readiness, risk mitigation, and executive progress reporting. Uses AI-driven tools to improve scheduling, forecasting, and project performance.

Leads complex customer-facing technical programs for AI storage computing platforms, coordinating OEMs, ODMs, vendors, software partners, engineering, operations, quality, product management, and sales. Drives system integration from proof of concept through development, validation, customer acceptance, and production deployment. Manages timelines, design reviews, technical issues, risks, metrics, dashboards, and executive communications while ensuring successful project execution and continuous improvement.

Lead strategic technical programs with CSPs and ODM/OEM partners to deploy NVIDIA AI datacenter platforms. Integrate datacenter tools, operationalize AI factory processes, resolve blockers, manage timelines and cross-functional teams, ensure delivery of customer-specific features, and communicate program status and risks to senior leadership.

The role involves integrating AI supercomputing systems into datacenters, collaborating with engineering teams, and producing documentation for processes related to datacenter integration and fit-out.

The Senior Technical Program Manager will lead the lifecycle for the Circuit Solutions Group, optimizing engineering workflows, handling complex dependencies, and driving operational excellence through schedule management and automation.

Lead end-to-end massive-scale data programs for NVIDIA’s Nemotron AI models, from acquisition and curation through release. Translate ML research needs into sourcing plans, establish data quality and compliance standards, manage inventory and IP clearance, and oversee annotation campaigns. Maintain roadmaps, track data velocity, manage risks, and align engineering, legal, operations, vendors, and ML researchers. The role emphasizes generative AI datasets, synthetic data, human-in-the-loop workflows, and evolving multi-stakeholder requirements.

Lead technical programs with hyperscalers and OEM/ODMs to deliver AI datacenter infrastructure from design through production. Define schedules and milestones, translate customer requirements into cross-functional plans, resolve issues, manage qualification/validation, monitor factory production and yields, and communicate program health to customers and leadership. Champion post-deployment sustaining support and coordinate global teams to ensure timely delivery and customer acceptance.

Lead end-to-end lifecycle of silicon-based products: plan, manage milestones, and ramp to mass production. Coordinate engineering, design, and marketing; own technical requirements, datasheets, and feature prioritization. Track progress, mitigate risks, report to senior leadership, and drive process improvements to ensure timely, on-budget delivery.

Lead end-to-end release management for Compute Platform Software: coordinate cross-team release activities, manage branching/version control, assess release readiness and risk, build automation and dashboards, define KPIs and schedules, work with engineering/QA/product/operations, drive post-release validation and continuous process improvements.

Lead end-to-end program management for NVIDIA Metropolis Vision AI products: drive roadmap execution, coordinate engineering and product teams, manage sprints and KPIs, use Jira/Confluence for reporting, and support model training, optimization, and edge deployment into production.

Leads and expands a Tribal College and University Computer Science and AI program. Responsibilities include program design, grant implementation, financial oversight, grantee monitoring, evaluation, donor reporting, partner and consultant management, advisory facilitation, curriculum and faculty development support, team supervision, fundraising proposals, strategic planning, and extensive site-visit and conference travel.

Leads Docker’s Forward Deployed Engineering program by defining delivery standards, quality metrics, operating rhythms, and engagement processes. Tracks customer and engineering commitments, manages dependencies and capacity planning, surfaces risks, communicates with executives, improves cross-functional collaboration, and mentors junior technical program managers. The role supports enterprise customers and requires strong knowledge of cloud platforms, containers, software delivery, and metrics-driven program management.

Leads a production portfolio across strategy, program delivery, financial forecasting, resource planning, supply-chain leverage, risk management, customer engagement, proposals, and technology investments. Oversees cross-site governance, PM coaching, portfolio reporting, compliance, configuration control, and continuous improvement while aligning programs with customer and corporate objectives.