Principal Solutions Architect

Principal Solutions Architect, Physical AI & Robotics Deployment

About Noble Machines

Noble Machines builds multipurpose robots to support human workers in the world's toughest jobs—turning dangerous work from a necessity into a choice. Our work demands reliability, robustness, and readiness for the unexpected—on time, every time. We're assembling a mission-driven team focused on delivering real impact in heavy industry, from construction and mining to energy. If you're driven to build rugged, reliable products that solve real-world problems, we'd love to talk.

About the Role

We're looking for a Principal Solutions Architect to help customers put Moby, our general-purpose robot, to work in their operations. You'll turn customer needs into achievable applications, customize and integrate the platform, and lead deployments from discovery through production and long-term adoption.

This is a customer-facing, high-ownership role that connects Engineering, Product, Sales, and Customer Success. You'll need a practical understanding of robotic perception, learning, and autonomous action, and the ability to explain capabilities, limitations, and deployment decisions clearly to engineers and executives alike.

You might come from robotics deployment, application engineering, autonomy, systems integration, or solutions architecture. Formal pre-sales experience matters less than proven ownership of real robot deployments and strong communication skills. As Noble Machines grows, this role can expand into building and leading an Application Engineering team.

What You'll Do

• Lead discovery and solution design.
• Learn customer workflows, operating environments, constraints, and business goals, and assess where Moby fits and what customization and integration it needs.
• Architect the deployment.
• Develop solution architectures, deployment plans, technical success criteria, and risk assessments.
• Set clear expectations.
• Present technical concepts, demos, and recommendations to engineering teams and executive stakeholders, and be candid about platform capabilities and deployment readiness.
• Own deployments end to end.
• Lead engagements from technical evaluation and proof of concept through pilot, production, and ongoing improvement.
• Customize and integrate Moby.
• Work with perception, learning, autonomy, and controls teammates to connect sensor inputs and task requirements to reliable robot behavior.
• Troubleshoot across the stack.
• Resolve hardware, software, sensor, and AI integration issues alongside Engineering.
• Prove performance.
• Define and validate measures for task completion, reliability, and failure recovery against agreed customer acceptance criteria.
• Close the loop.
• Partner with Sales on evaluations and proposals, turn customer requirements into actionable work for Engineering and Product, and bring field findings into the roadmap.
• Build for scale.
• Create repeatable deployment methods, documentation, and best practices, and mentor colleagues as the Application Engineering function grows.

What You'll Bring

• Bachelor's degree in Engineering, Computer Science, Robotics, or a related field, or equivalent hands-on experience.
• Personal ownership of AI-enabled physical robot deployments, with clear examples of your technical contributions, decisions, and results.
• Practical experience with robotic perception, learning, and autonomous behavior in real-world applications.
• Working understanding of vision-language-action (VLA) models and how visual inputs, task instructions, and learned behaviors translate into robot actions.
• Experience integrating and troubleshooting robotic hardware, software, sensors, and AI capabilities.
• A track record of taking deployments from evaluation or pilot to reliable operation, including the challenges you hit and how you solved them.
• Exceptional communication and presentation skills, with credibility in front of customers, engineers, and executives.
• Ability to work across technical and commercial teams in a fast-moving, early-stage environment.
• Willingness to travel to customer sites and to work on-site in Sunnyvale regularly.
• Candidates with fewer years of experience are encouraged to apply if they bring the technical depth, deployment ownership, and communication skills above.
• Nice to Have
• Advanced degree in Robotics, Computer Science, Engineering, or a related field.
• Experience deploying humanoids, autonomous mobile robots, mobile manipulation, or other AI-enabled physical systems.
• Hands-on experience integrating, adapting, or evaluating VLA models, learned policies, or perception systems on physical robots.
• Experience with simulation, robot learning workflows, and sim-to-real transfer.
• Experience leading customer discovery, technical demos, proofs of concept, or enterprise solution design.
• Experience supporting industrial customers in construction, mining, energy, manufacturing, or logistics.
• Experience mentoring engineers or building an Application Engineering team.
• California Pay Transparency Statement

Pay Transparency & Compensation: In accordance with California's Pay Transparency Act (SB 1162), the expected base salary range for this position located in Sunnyvale, CA is $200,000 – $350,000 per year, in addition to bonus, equity, and benefits.

Actual compensation within this range will be determined based on several factors, including the candidate's qualifications, relevant experience, technical skills, and specialized expertise. Base salary is just one component of Noble Machines' total rewards package, which may also include equity options, comprehensive healthcare benefits, retirement plan contributions, and performance-based incentives. Relocation assistance may be available.

Exceptional U.S.-based candidates who need an alternative location arrangement will be considered individually.

Equal Opportunity Employer

How to Apply

Share your resume and one or two deployments you personally owned. Tell us what the customer needed, the decisions you made, what went wrong along the way, and how the robot performed in production.