About Us

At Archetype AI, we’re building the world’s first physical AI platform to bring artificial intelligence into the real world. Our foundation model, Newton, understands the physical world through objective sensor data and generates real-time insights into complex physical behaviors, from industrial machinery and systems to wearable devices and smart environments.

Formed by a high-caliber team from Google and backed by one of Silicon Valley’s most renowned venture funds, Archetype AI is at Series A and rapidly advancing its technology for the next big leap. This is a unique opportunity to join an exciting, fast-growing AI team based in the heart of Silicon Valley.

About the Role

Our customer programs combine emerging AI technology, evolving customer needs, and cross-functional teams across Solutions, Research, Product, and Engineering. This role creates clarity out of that complexity, turning technical discussions and customer goals into aligned plans, decisions, and actions so engagements stay on track from initial scope through production.

What You’ll Own

• Customer programs reach pilot, production, and expansion against clear success criteria.

• Customer goals and engineering work stay aligned through clear milestones, dependencies, and decisions.

• Technical risks, gaps, and unresolved issues have clear paths forward aligned across the responsible teams.

• Cross-functional blockers and tradeoffs reach resolution without losing program momentum.

Key Qualifications

• 5+ years leading technical programs, customer implementations, or enterprise deployments.

• Track record of turning ambiguous goals into successful outcomes without a predefined execution path.

• Experience leading engagements directly with enterprise customers and senior stakeholders.

• Technical fluency with AI/ML, data, cloud, APIs, or similarly complex software systems.

Nice to Have

• Hands-on background in engineering, solutions engineering, or systems integration.

• Track record delivering AI/ML or data-centric products in real-world environments.

• Experience with edge computing, sensors, industrial systems, or time-series data.