nTop generates and validates mission-ready geometry automatically, freeing engineers for the decisions that matter. Backed by Insight.
About the role
We're looking for an Engineering Manager to build and lead the team responsible for workload orchestration — the infrastructure that lets nTop customers define, launch, monitor, and collect results from large-scale distributed computation jobs. This team will be small by design : senior engineers, AI-native workflows, high individual leverage. We'll grow when the work earns it. One founding engineer is in place; you will hire and lead the rest while contributing to systems spanning
What they're looking for
- 7+ years of software engineering experience, including 3+ years managing engineering teams, experience building and shipping distributed systems or infrastructure software
- Hands-on expertise with Docker, Kubernetes, and at least one cloud platform (AWS, GCP, or Azure), deep understanding of job scheduling and compute-intensive workloads at scale
- Experience shipping into customer-managed environments — on-prem, hybrid, or air-gapped
- Track record of building teams : recruiting, developing, and making hard performance calls
- Strong collaboration skills with PMs, designers, and field engineers, able to reason about customer value, not just technical elegance
More about this role
nTop builds parametric design software for the hardest geometry problems in aerospace, defense, and industrial turbomachinery. Our platform lets engineers define a design as a parametric program — not one aircraft or turbine, but every variant a program might need. The next step is scale: thousands of design variants evaluated in parallel, across cloud, HPC, and on-prem infrastructure, feeding directly into AI-driven optimization workflows. We're building the product that makes that possible.
We're looking for an Engineering Manager to build and lead the team responsible for workload orchestration — the infrastructure that lets nTop customers define, launch, monitor, and collect results from large-scale distributed computation jobs.
This team will be small by design : senior engineers, AI-native workflows, high individual leverage. We'll grow when the work earns it. One founding engineer is in place; you will hire and lead the rest while contributing to systems spanning
- containerized headless execution,
- job scheduling,
- integration with third-party platforms (HEEDS, ModelCenter, PhysicsX Flux — MDO and simulation workflow platforms our customers already rely on),
- and...
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