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Archetype AI is building the world's first physical AI platform that brings artificial intelligence into the real world. The company's 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. Founded by a high-caliber team from Google and backed by a renowned Silicon Valley venture fund, Archetype AI is in Series A and rapidly advancing its technology.
As a Customer Success Manager, you will lead customer programs that combine emerging AI technology, evolving customer needs, and cross-functional teams across Solutions, Research, Product, and Engineering. You will create clarity out of complexity, turning technical discussions and customer goals into aligned plans, decisions, and actions that keep engagements on track from initial scope through production.
Key responsibilities include:
- Guiding customer programs to reach pilot, production, and expansion against clear success criteria
- Keeping customer goals and engineering work aligned through clear milestones, dependencies, and decisions
- Identifying technical risks, gaps, and unresolved issues and establishing clear paths forward aligned across responsible teams
- Resolving cross-functional blockers and tradeoffs without losing program momentum
This role requires strong program management skills, the ability to navigate ambiguity, and deep technical fluency. You will work directly with enterprise customers and senior stakeholders, translating between business objectives and technical execution.
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
