Solutions Engineer, Physical AI

Solutions Engineer, Physical AI

Join a Palo Alto AI startup building interactive AI concierges for airports, live events, and retail spaces. Imagine a traveler asking a kiosk for directions and scanning a QR code to take the route with them. As a Solutions Engineer, you’ll demo experiences like this to customers, write the integration code, and lead onsite deployments from testing through go-live.

This is a hands-on engineering role. You’ll ship production code, set up hardware and networking onsite, and explain how the system works to audiences ranging from engineering teams to customer executives.

Location
Palo Alto, CA · Onsite

Employment
Full-time

What You’ll Do

• Lead multiple customer deployments from scoping and testing through installation, launch, and follow-up.
• Write production code in Python, JavaScript, or TypeScript. Build and troubleshoot APIs and integrations that connect AI agents with customer systems.
• Install and configure displays, sensors, networking gear, and edge computing devices. Diagnose hardware, connectivity, and software issues in live environments.
• Lead product demos and technical presentations for customers, partners, and executives, including at public events. Explain technical tradeoffs and next steps in plain language.
• Bring feedback from deployments to Product and Engineering to improve the software, hardware, and rollout process.

What You’ll Bring

• Experience delivering customer-facing enterprise software or technical implementations and taking responsibility for go-live.
• Hands-on coding ability in Python, JavaScript, or TypeScript, with examples of software or integrations you’ve shipped.
• Strong spoken and written communication, including the ability to present live demos and answer questions from technical and executive audiences.
• Ability to manage several customer projects, follow through on commitments, and troubleshoot under pressure.
• Willingness to work hands-on with displays, sensors, networking, and other onsite equipment.
• Interest in how large language models, computer vision, and multimodal AI work in production.

Preferred Qualifications

• Enterprise software delivery at a startup or technical implementation experience at a consulting firm.
• Experience with LangChain, LlamaIndex, prompt engineering, or retrieval-augmented generation (RAG).
• Familiarity with edge computing, IoT, AV systems, or robotics.
• A background in computer science, electrical engineering, information systems, or a related technical field.

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