Responsibilities
- Product Vision: Define the roadmap for our doctor facing Design product—evolving our 1st-party internal design software into a doctor-friendly interface that feels intuitive
- Bridge Internal & External: Deeply understand the workflows of our internal design workforce to identify which "levers" of the CAD process should be exposed to doctors for influence (anatomy, margins, occlusion, and shade).
- Cross-Functional Leadership: Serve as the connective tissue between CAD Engineering, ML, UX Design, and Manufacturing to ensure "what the doctor sees is what gets printed."
- Conduct customer discovery, market research, and competitive analysis to inform roadmap decisions and identify opportunities to innovate.
- Manage the full product lifecycle, from ideation to launch and iteration, in a highly agile and collaborative environment.
- Use data and qualitative insights to measure impact, communicate results, and continuously refine the product direction.
Requirements
- 5+ years of experience in product management, managing software products through the full lifecycle from MVP to general release and subsequent iterations
- The "Translator" Ability: You can take a complex, internal-only technical tool and strip away the "noise" to create a simplified, powerful experience for a non-technical expert (the Doctor).
- 3D/Graphics Fluency: You understand the constraints and possibilities of rendering 3D assets in a web or app environment.
- High Bias-to-Action: You thrive in hyper-growth environments and are comfortable moving from high-level strategy to "nitty-gritty" specs in the same afternoon.
- Clinical Empathy: You are obsessed with the end-user. You want to spend time in dental offices understanding how a doctor wants to interact with a digital restorative.
Nice to Have
- 0-1 Experience: You have previously taken an internal tool and successfully productized it for external customers.
- Industry Context: Previous experience in Dental, MedTech, or sophisticated "Pro-sumer" creative tools.
- Technical Background: Experience as a software engineer or a deep understanding of ML model deployment.
