Robotics Software Engineer II

About the Role

We are looking for a hands-on Robotics Software Engineer to join our Skills team, focused on developing, testing, validating, and integrating robot skills into real customer workflows. In this role, you will operate at the boundary between prototype and production, working directly with our humanoid robot to evaluate performance, root-cause failures, and collect targeted teleop data to improve learned behaviors. You will be hands-on with hardware nearly every day, helping bring new customer workflows online and ensuring existing deployments remain reliable. You will define test plans, execute experiments, and validate that our behaviors meet autonomy and performance requirements. You’ll also partner with AI teams to refine learned policies using real-world data.

Key Responsibilities

Develop Behaviors for Humanoid Robots & Integrate into Workflows

• Develop and maintain the core library of production-ready skills that form the foundation of customer workflows.
• Script new skills using behavior trees, state machines, or task planners, defining control flow logic and behavior sequencing.
• Deploy classical as well as modern robotics paradigms to implement robot “skills” in order to complete variety of tasks in target domains
• Build and maintain workflows using the robot’s skill API.
• Prototype new skills and customer use cases to assess their feasibility.

Enable Human-in-the-loop Interventions

• Develop the components needed to allow robots to recover from anomalous situations with human oversight
• Build the data collection pipeline to analyze and catalog task errors, and improve the robot “skills” toolset to resolve these task errors autonomously.
• Create the infrastructure needed to minimize the frequency and duration of interventions where a human is in the loop while maximizing the reach of a single human “resolver” across the humanoid fleet.

Testing, Validation & Deployment

• Define what “production-ready” means for each skill or workflow and design the test plans and infrastructure to validate it.
• Recreate corner cases from logs and failures into repeatable tests.
• Validate new skills and workflows both in simulation and on hardware before release.
• Travel occasionally (<10%) to customer sites to assist in deployment, perform hands-on validation, and support tuning efforts.

About You

• 2+ years of relevant experience, including research-level and industry experience, preferably applied to mobile manipulation robots 
• You have a B.S. or M.S. in Robotics, Computer Science, or a related field.
• You are proficient in Python and write clean code.
• You have experience with Linux systems.
• You are excited about developing physical robot behaviors, not just running simulations. You enjoy getting your hands dirty, iterating on hardware, and watching your work come to life in the field.
• You are curious about how autonomous robots work end-to-end, from low-level control to high-level task planning, and want to help bridge the gap between behavior design and real-world deployment.
• You have a strong sense of ownership and pride in the reliability of your work. You sweat the details and are always looking to eliminate failure modes.

Bonus Qualifications

• Prior experience scripting robot behaviors using state machines, behavior trees, or other control flow logic.
• Understanding of robot manipulation, motion planning, and kinematics (e.g., familiarity with MoveIt framework).
• Hands-on experience collecting and curating teleop datasets for training or evaluating learned policies.
• Experience developing AR/VR applications for robot teleoperation.
• Exposure to test-driven development, automated regression testing, and CI/CD workflows.
• Experience operating autonomous robots in customer environments or real-world deployments.

This position is located at one of our offices in Pittsburgh, PA or Salem, OR or San Jose, CA (any Agility Robotics office). On-site minimum 4 days/week.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.