Deliver the transition. Lead the team through the rendering pipeline modernization, the launch of generative model creation through our notebook API, and the shift of engineering effort from the legacy desktop UI toward the new product, without dropping the quality of what customers depend on today. What Success Looks Like 90 days: You know each engineer's strengths and goals, and each has a development plan. Every active workstream has an owner, a scope, and a next step that the team and the PM can see.
You have absorbed enough of the technical landscape to hold a design discussion on modeling and rendering topics. 12 months: The team ships on the cadence 2027 demands, and multi-month projects land on the timelines you set. The rendering pipeline modernization is well underway and the team has meaningfully shifted toward the new product. Each engineer can articulate where they stand and where they're headed. Who You Are Required 3+ years managing software engineers, with a track record of coaching senior individuals to higher performance, setting clear expectations, and having the direct conversations that come with the job.
A background in graphics, geometry, or a closely adjacent computational field. A PhD is not required, but you must play well with a team that lives deep in implicit geometry, GPU rendering, and computational math. Fluency in C++, with the ability to read, reason about, and review code in a large, mature codebase. Rust experience is a strong plus. A track record of structured project management across many concurrent topics: keeping work visible, prioritized, and finishing on the timelines you commit to.
Demonstrated adoption of AI-assisted development in a team you led, and a point of view on how it changes an engineering organization's tempo. Experience managing a distributed team across US and European time zones. Preferred Hands-on experience with GPU shader languages (GLSL, HLSL, or similar) or modern graphics APIs, and with modernizing a rendering pipeline. Experience carrying a desktop-native product to new surfaces such as the web browser or mobile.
Familiarity with CAD, CAE, or other engineering software and the workflows around it. Experience integrating generative AI into a product — not building models, but giving an AI something to grab onto and refining its output against expert judgment. Why This Role You'll lead the team that owns the core of nTop — the modeling technology every other capability depends on — at the moment it moves from a desktop application to a generative, multi-surface product.
The engineers are world-class, the problems are hard, and the ownership is real. nTop is an equal opportunity employer committed to building a diverse and inclusive team. Please note that nTop may use AI products to assist in the recruiting process. All resumes are reviewed by, and all employment decisions are made by, nTop's Hiring Team. If you require a reasonable accommodation during the interview process, please don't hesitate to email us directly.