Manager, System Software Engineering - Infrastructure Engineering and Automation

Overview

Lead and grow infrastructure and validation engineering teams supporting NVIDIA's Local AI and PC gaming R&D, defining the infrastructure and validation strategy for current and next-generation platforms.

What you'll do

• Lead and grow infrastructure and validation engineering teams responsible for CI/CD, test development and automation, regression analysis, failure triage and debugging support, and lab operations, including hardware health, maintenance, and recovery.
• Define and drive the team's technical roadmap, priorities, and delivery commitments across Local AI and PC gaming, balancing long-term infrastructure improvements with day-to-day engineering needs.
• Drive the development and deployment of tests and benchmarks that reflect real-world usage, supported by automation for environment setup, test execution, log collection, and results analysis.
• Build tools that help reproduce failures and analyze logs and system metrics.
• Partner with engineering teams to identify root causes and resolve functional issues and performance bottlenecks across the hardware and software stack.
• Ensure build systems, CI pipelines, test orchestration, and hardware labs are reliable and scalable.
• Plan staffing, hardware capacity, schedules, and investments with infrastructure, security, and operations partners.
• Communicate strategy, progress, risks, and technical trade-offs to engineering teams and senior leadership.
• Partner with graphics, driver, platform, Local AI, product, and open-source teams to define requirements, align priorities, resolve dependencies, and deliver infrastructure that accelerates engineering productivity.

What you'll need

• Bachelor's or master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related technical field, or equivalent experience.
• Minimum 3 years of experience in management and 10+ years of relevant software engineering experience, including substantial system software, platform, runtime, or systems infrastructure development.
• Proven record of managing large, high-performing software teams, setting direction, developing engineers, and delivering results through teams.
• In-depth knowledge of system programming and operating systems concepts, including APIs, processes and threads, concurrency, memory and resource management, and software–hardware interaction.
• Experience designing, debugging, profiling, or optimizing software across system boundaries, using instrumentation and performance data to improve correctness, reliability, and efficiency.
• Experience setting technical strategy and operational goals, leading multi-team engineering programs, and balancing staffing, capacity, schedules, and investments.
• Ability to communicate technical decisions to senior stakeholders and align partners across software and hardware disciplines.

Nice to have

• Background with graphics software, GPU or device-driver stacks, DirectX, or Windows platform bring-up.
• Experience integrating or debugging local AI inference frameworks such as llama.cpp, Ollama, PyTorch, vLLM, or Windows ML; familiarity with CUDA or GPU programming is a plus.
• Experience building system software, runtimes, developer tools, test frameworks, or benchmark infrastructure used across diverse hardware configurations.
• Experience with system profiling, performance optimization, telemetry, diagnostics, or analysis of CPU and GPU workload behavior.
• Contributions to open-source software or experience supporting developer-facing software infrastructure and hardware-backed validation.