Senior Software Engineer, Agentic Robotics Infrastructure

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Software Engineer to build the platform for Physical AI robots, focusing on agentic infrastructure. This role involves designing, building, and testing agent skills, automated workflows, and embedded agents, as well as owning CI/CD pipelines for robotics applications. The goal is to ensure the software stack is ready for use by various types of agents, from coding assistants to embedded systems on robots.

What you'd actually do

  1. Design for it. Shape APIs, error surfaces, tooling, and documentation so that agents can build with our robotics stack as effectively as human engineers — across multiple products and neighboring teams.
  2. Build for it. Create agent skills and automated workflows that teams adopt in their own repos, and support embedded agents on the robot (code-as-policy and related approaches) where latency, safety, and determinism constraints apply.
  3. Test for it. Run and integrate skill evaluations so agentic workflows are measured, not just deployed, and turn those evaluations into automated checks that catch regressions before they land.
  4. Build the infrastructure that keeps it true. Own CI/CD across the applications repos — spanning CMake, Bazel, and Python builds — including runners, Docker images, dataset provisioning, nightly builds, and release and docs pipelines.
  5. Spread what works. Package patterns into docs, templates, and starter kits, then drive adoption — running the conversations with teams and following through until a practice is live in more than one repo.

Skills

Required

  • Master's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience)
  • 5+ years of professional software engineering experience
  • Fluency across the kinds of software a robotics stack is made of — policy training, simulation, on-robot deployment
  • Hands-on experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, or similar)
  • proven Docker and Linux fundamentals
  • Practical experience using coding agents or LLM-based developer tools in real work
  • Clear written communication

Nice to have

  • Experience building agent skills, tool integrations, or MCP servers, and evaluating agent performance systematically
  • Familiarity with NVIDIA robotics products such as Jetson, Isaac Sim/Lab, or Isaac ROS
  • Background in robotics, embedded systems, or another domain where software has to run on real hardware
  • Experience managing GPU-backed CI infrastructure or self-hosted runner fleets

What the JD emphasized

  • agents can build with our robotics stack as effectively as human engineers
  • embedded agents on the robot
  • agentic workflows are measured
  • agent skills, tool integrations, or MCP servers, and evaluating agent performance systematically

Other signals

  • building agentic systems
  • robotics infrastructure
  • CI/CD for AI agents