Overview

You turn customer problems into structured, repeatable Product Solutions. Clear use cases, well-defined engagements, and product inputs that connect what the field needs with what we build next.

Our buyers come with messy, technical problems across robotics, data, and evaluation. They know something is broken or expensive, but not how to express it as a product need. You own that translation. You sit between the customer, Product, Research, Engineering, and Delivery, turning each engagement into something structured, reusable, and productizable.

What You Will Do

• Technical discovery and problem structuring: understanding a customer's data, evaluation, or policy problem and mapping it to a clear solution pattern rather than a one-off engagement.
• Engagement design: defining what data comes in, what the platform runs, what we deliver, and what success looks like, in both customer language and internal terms.
• Solution standardization: turning repeated engagement patterns into templates, playbooks, and reusable solution designs instead of bespoke work.
• Customer interpretation layer: explaining outputs and results in a way customers trust and can act on, translating technical signals into operational meaning.
• Product feedback loop: identifying patterns across customers and turning them into concrete product requirements, features, and roadmap inputs.
• Pre-sales technical shaping: partnering with GTM to scope engagements correctly, set expectations, and ensure what we sell is aligned with what we can productize.

What We're Looking For

• Strong technical customer-facing experience: solutions engineering, product solutions, or technical strategy, ideally for data or machine learning systems.
• Ability to structure ambiguity: you can take a vague problem and turn it into a clear, repeatable approach.
• Product instinct: you naturally look for patterns, abstractions, and what should become part of the product rather than staying custom.
• Credibility with technical buyers and clarity in communication with non-specialists.
• Willingness to be close to customers and own the shape and success of engagements.

Nice to Have

• Robotics, computer vision, or machine-learning-data domain experience.
• Experience turning services or custom work into productized offerings.
• Early-stage or zero-to-one environment where roles were not predefined.