Software Engineer, Workload Orchestration (Distributed Compute))
US Remote / Germany / United KingdomRemotefull-timelead
Software EngineerSoftware Engineering
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Quick Summary
Key Responsibilities
extracting a subsystem from our C++/Python monolith behind a clean interface, building a path for submitting and scheduling workloads on cloud or on-prem clusters,
Technical Tools
Software EngineerSoftware Engineering
nTop builds computational design software for engineers designing next-generation aircraft, defense systems, and performance vehicles. Our platform uses fundamentally different approaches to geometry representation and computation, enabling designs traditional CAD systems cannot express. Our teams include world-class specialists in computational geometry, meshing, rendering, and simulation. We're looking for an engineer who can work across those domains and help us make the system underneath them faster, more open, and easier to build on.
You'll join our Orchestrate team as a senior engineer working on one of our biggest shifts: turning an installed desktop application into a platform that can run computation in parallel across on-prem and cloud clusters, and opening up how designs are stored.
You'll start by owning projects end to end. You decide what "done" looks like, break the work into tasks, keep it moving, and pull in the teams you depend on. As you build context, you'll take on open-ended platform problems where nobody yet knows the answer: you'll research the options, recommend a path, and turn it into projects. Sometimes the right recommendation is "not yet," and we want you to say so.
- Projects (1-3 months). Platform work with a clear goal that you scope and drive to done. Examples: extracting a subsystem from our C++/Python monolith behind a clean interface, building a path for submitting and scheduling workloads on cloud or on-prem clusters, or moving part of our file format toward an open, text-based structure.
- One open platform problem (1-3 quarters). A question the team knows matters but can't yet answer, such as how to run thousands of parallel simulation jobs reliably across mixed on-prem and cloud GPU environments. You investigate, prototype, compare approaches and trade-offs, and recommend what to build.
- Cross-team delivery. Your projects touch our other engineering teams and the domain specialists who built much of the codebase. You keep those dependencies moving and make sure everyone knows how your work connects to theirs.
- Quality and speed. Better tests, clearer interfaces, and faster feedback loops in the code you touch, so the next engineer has an easier time.
- First 3 months: Learn the codebase and who depends on it. Deliver a first scoped project with a defined finish line.
- By month 6: Own a larger cross-team project from design through deployment, with your plan, status, and trade-offs visible to the people relying on it.
- By month 12: Own an open platform problem. Present a researched recommendation, and drive at least one resulting project into production.
Your impact is measured by how dependably you deliver what you own, and by how much easier you make the work of the engineers around you.
Required
- 6+ years of professional software engineering, with a record of owning projects end to end and delivering across team boundaries.
- Strong C++ experience building production systems; comfortable working in Python as well.
- Hands-on experience with distributed or parallel systems, such as job scheduling, workload orchestration, cluster or cloud compute, or fault-tolerant services.
- Experience improving a large, long-lived codebase step by step: refactoring, API design, or extracting modules without breaking existing users.
- Comfort with ambiguity. You can take a fuzzy problem, research it, weigh options, and make a clear recommendation, including "not yet."
- Clear written and spoken communication. You earn trust across teams by explaining your reasoning and following through.
- A habit of helping teammates grow, through code review, documentation, and pairing.
Valued
- High-performance computing, GPU workloads, or scientific computing
- File format, serialization, or protocol design
- Programming language or domain-specific language tooling; exposure to Rust
- CAD/CAM, simulation, or aerospace and manufacturing software
- Working with technically sophisticated customers
- You want every task defined for you before you start. Here you scope your own work.
- You prefer to stay deep in one narrow specialty rather than work across the platform.
- You're looking to set company-wide technical direction for several years from day one. If that's you, let's talk about other roles.
Work on hard computational problems in geometry and high-performance computing, with real impact in aerospace and advanced manufacturing. Own meaningful pieces of a platform that is defining a new category, alongside deep specialists who will teach you their domains.
What We Offer
~1 min readThe base pay range for this role is $165,000 – $215,000 per year.
Location & Eligibility
Where is the job
Worldwide
Fully remote, anywhere in the world
Who can apply
Same as job location
About this job
- Pay per year
- $165,000–$215,000 a year
- 1% above the $187,500 median for Software Engineer jobs on Jobera (7,202 salaries).
- Posted
- 22 days ago
Listing Details
- Posted
- October 20, 2026
- First seen
- October 20, 2026
- Last seen
- November 11, 2026
Posting Health
- Days active
- 21
- Repost count
- 0
- Trust Level
- 40%
- Scored at
- November 11, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
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