Lead a distributed team responsible for nTop’s modeling and rendering technology. Coach senior engineers, structure concurrent technical workstreams, improve development velocity, partner with Product Management on execution, and guide modernization of the rendering pipeline and transition from desktop software to AI-assisted, multi-surface products. The role requires technical fluency in graphics, geometry, computational math, C++, and GPU rendering, along with experience managing distributed engineering teams.
About nTop
The Role
What You'll Do
What Success Looks Like
Who You Are
Why This Role
nTop builds parametric design software for the hardest geometry problems in aerospace, defense, propulsion, and industrial energy. Our platform lets engineers define a design as a parametric program — not one aircraft or turbine, but every variant a program might need — and explore design spaces that were previously too large to search. The next step is generative: describe the part you need, and let AI produce a sophisticated, engineering-grade nTop model in minutes. We're building the product that makes that possible.
We're looking for an Engineering Manager to lead the team that sits at the beginning of everything nTop does: Modeling & Rendering. This team owns our core implicit modeling technology and the tools an engineer uses to create, modify, and visualize a model — whether they build it by hand in the application or generate it with an AI tool such as Astra or Fable. It also owns how those models flow into the broader ecosystem of CAD and PLM tools our customers already rely on. If the rest of nTop is a chain, this team is the first link, and the beating heart of what we've built and what we're building next.
The team is small, senior, and deep. Its engineers are industry experts in implicit geometry, GPU acceleration, and rendering, and they are the people who made it possible for an AI to skip manual modeling and go straight to a generative result — including refining what a good model looks like so the AI produces one. The team is distributed across Europe and the US, and you will be managing across time zones from day one. You will be managing across time zones from day one.
The team's charter is evolving. Today it owns the modeling and rendering core of a mature, high-performance desktop application. Over the coming year it will increasingly build for a new generation of nTop — AI-assisted, and designed to reach engineers on more surfaces than the desktop — while modernizing the rendering pipeline underneath both. You'll lead the team through that shift.
You'll partner with a dedicated Product Manager who owns strategy and roadmap for this area. Your job is execution: how the team operates, how decisions get made, and how a high variety of unrelated technical topics stays visible, prioritized, and moving.
Coach a team of experts. Senior engineers with deep specialties don't all need the same thing from a manager. You will get to know each person's strengths and goals, tailor how you support them, set clear expectations, and give direct feedback that helps every engineer on the team do the best work of their career.
Bring structure to a wide topic mix. The team carries many workstreams at once — implicit modeling, rendering, UI, the execution kernel, AI integration. Keeping all of it visible, prioritized, and moving is the core of the job. You will give each project a clear scope, a clear next step, and a clear definition of done, and keep multi-month efforts on course by spotting drift early and making the call.
Set the operating tempo. nTop's R&D mandate for 2027 is to move an order of magnitude faster between identifying a market need and resolving it. You will eliminate micro-delays and toil, automate what can be automated, bring decision frameworks to technical debates so they end in a decision, and lead the team's adoption of AI-assisted development as a normal part of how work gets done.
Hold your own technically. You do not need to be the best geometer in the room, but you do need to follow an argument about implicit math, GPU rendering, or kernel architecture, ask the question that exposes the weak spot, and say no with a good reason. The team's engineers are experts, and they will value a manager who engages with the substance.
Be the PM's partner and proxy. "Work closely with Product Management to turn roadmap into engineering plans. Bring pre-structured decisions — options, trade-offs, and what needs deciding — and own day-to-day technical calls so the team keeps moving between checkpoints.
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.
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.
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.
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.
CompensationThe base pay range for this role is $265,000 – $295,000 per year.
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.
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