Engineering Manager, Distributed Computing Platform

About NTop

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.

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

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 deployment across environments from GPU workstations to cloud-scale Kubernetes clusters.

You'll partner with a dedicated Product Manager who owns strategy and roadmap for this area. Your job is to own technical execution: system design, team operations, and delivery into environments shaped by IT governance, export control, and heterogeneous infrastructure.

The north-star metric: headless nTop notebook executions. A notebook is a parameterized nTop program; headless means executing it without a user at the keyboard — more design variations explored, in less time, without a human in the loop.

What You'll Do

Build the team.

Recruit, hire, and develop a small, senior engineering team. Set clear expectations, give direct feedback, and establish practices that reflect nTop's engineering culture and the demands of infrastructure work.

Define the technical approach.

Own the architecture for headless execution and workload orchestration within the product direction set by the CTO and PM. Drive build vs. integrate vs. partner decisions for the systems your team owns, across workstations, on-prem HPC, and cloud.

Write code, especially early on.

This is a player-coach role. In year one, you'll be hands-on — writing production code, reviewing PRs, making architectural decisions alongside your team.

Ship integrations.

Lead execution on integrations with HEEDS, ModelCenter, PhysicsX Flux, and cloud-native job services. Deliver the headless pipeline: job definition, submission, monitoring, failure handling, and results collection.

Partner with Product.

Work with the Product Manager to translate product strategy into engineering plans. Provide grounded technical input on feasibility, sequencing, and risk. Push back when plans don't account for real constraints; propose alternatives when they don't.

Deliver for customers in hard environments.

Our customers are defense contractors, aerospace OEMs, and industrial manufacturers. You'll engage directly with their engineering and IT teams to design systems that work within real constraints — not around them.

90 Days

What Success Looks Like

You've assessed the technical landscape, aligned on the initial architecture with the CTO, and begun hiring. You've met with at least two or three customer IT or engineering teams firsthand.

12 Months

The team is staffed and delivering. At least one major integration is live. The headless execution pipeline is in production with a design partner (a strategic early customer co-developing with us). Team engineering practices — CI/CD, testing, incident response, deployment — are established and working.

Required

Who You Are

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

Preferred

HPC, scientific computing, or engineering simulation background (Slurm, PBS, HEEDS, ModelCenter, OpenMDAO)

Experience building for customers with ITAR/EAR obligations or strict IT governance

Familiarity with consumption-based pricing transitions

Comfort reading and reasoning about C++ codebases

Why This Role

You'll build a team and product area from scratch, reporting to the CTO, on problems that are genuinely hard and customers who care deeply. The shift from individual-engineer CAD to large-scale parallel computation is one of the most consequential transitions in engineering software — and this role sits at the center of it.