Customer Success Manager

Archetype AI•Palo Alto, CA

21h

About The Position

Archetype AI is hiring a Customer Success Manager (CSM) to own delivery and customer success across client engagements. Reporting to the Head of Solutions Engineering, this role is responsible for ensuring Physical AI solutions move from kickoff to production with clear plans, strong execution, and consistent outcomes. The CSM sits at the center of customer delivery and the broader GTM motion, partnering closely with Account Executives, Solutions Engineering, Product, TPM, and Platform teams. They run customer cadence, track progress and risk, and ensure signals from real-world deployments directly inform product direction and Solutions investments. The role also helps manage the internal Solutions Engineering backlog related to tooling, physical agent development, demos, and early applications.

Requirements

5–8+ years of experience in customer success, technical delivery, solutions, or program management roles.
Proven experience owning enterprise customer engagements from kickoff through production.
Strong cross-functional coordination and delivery execution skills.
Technical fluency and hands-on comfort running code, validating behavior, and triaging issues.
Excellent written and verbal communication skills.
High ownership mindset and comfort operating in fast-moving, ambiguous environments.

Responsibilities

Own customer engagements from kickoff through production, including delivery plans, milestones, readiness, and risk management.
Run customer cadence, including regular delivery calls, status updates, and executive reviews.
Partner closely with Solutions Architects and Solutions Engineers, who own technical leadership, while coordinating overall delivery.
Ensure high-quality onboarding, enablement, and successful adoption of Physical AI applications.
Act as a primary point of coordination for customer issues, questions, and requests, driving resolution through the appropriate teams. Navigate the real world challenges of physical deployments, such as sensor data quality and hardware constraints.
Partner closely with Account Executives throughout the customer lifecycle to ensure aligned expectations, smooth handoffs, and clear accountability.
Support deal execution by contributing delivery context, scoping input, and sequencing recommendations for QSTs, POCs, pilots, and production.
Serve as connective tissue across the GTM team, ensuring Sales, Solutions, and Delivery remain aligned as engagements evolve.
Help maintain a clear, shared view of customer health, delivery status, and risks across GTM stakeholders.
Support Account Executives to identify expansion opportunities within existing accounts to drive renewals and prevent churn.
Coordinate work across Solutions Engineering, Product, TPM, and Platform teams.
Escalate technical, delivery, and support-related issues appropriately to ensure timely resolution.
Translate customer feedback, issues, and requests into clear, actionable inputs for internal teams.
Capture, synthesize, and prioritize feature requests arising from customer engagements.
Translate customer needs and delivery learnings into well-formed feature requests and problem statements.
Partner with Product and Engineering to ensure customer-driven requirements are clearly understood and tracked.
Close the loop with customers and GTM stakeholders on feature progress and outcomes. Translate technical milestones into business ROI for customers' executives, helping them justify long-term investments and expansion.
Manage the internal Solutions Engineering backlog for tooling, physical agents, demos, and early applications.
Prioritize work based on customer impact, delivery needs, and strategic value.
Track progress, dependencies, and outcomes across internal Solutions initiatives.
Help drive repeatable delivery patterns and reusable assets.
Maintain strong technical credibility with customers and internal teams.
Run code, validate integrations, and file high-quality bugs and issue reports when needed.
Understand how customers interact with Physical AI applications, APIs, SDKs, and deployments, without acting as a full-time engineer.