Senior Aerodynamics & Flight Sciences Engineer

Sitreps•Denver, VA

12d•Onsite

About The Position

The client builds a family of low-cost, high-altitude and long-range systems: stratospheric balloon platforms, balloon-deployed ISR and communications buses, autonomous glide vehicles and dispensers, and a family of ultra long range (ULR), affordable-mass, ground-launched one-way attack and ISR drones. The company has closed a recent funding round backed by a top-tier venture syndicate, and its systems are flying and being tested in operationally relevant environments today, including active flight test campaigns forward-deployed overseas. The team is small, moving fast, and every engineer owns hardware that flies. You will own the aerodynamic model and outer mold line for the client's ULR airframes: body shape, control surfaces, static margin, stability and control derivatives, and the pipeline that turns geometry into the coefficient tables that the 6-DOF and flight software consume. Hands-on and end-to-end — low-fidelity sizing through CFD, wind tunnel, and flight test correlation. Just as important: you will own how flight sciences data moves through the company. They want someone who has seen what a modern test data stack looks like — real-time telemetry capture, automated test orchestration, contextualized datasets, instant post-test review — and can build that discipline in from the start rather than bolting it on at 200 people. If you have used or built on platforms like Nominal Core or Connect, or written the internal tooling that turns raw wind tunnel and flight test data into a design decision the same day, that experience is directly on point here. They are equally interested in how you use modern AI tooling. Agentic coding assistants, AI-assisted CFD pre/post and mesh generation, surrogate and reduced-order models trained on test data, LLM-driven analysis over test archives — these are not treated as novelties. An engineer who leverages them well produces multiples of the design iterations of one who does not, and they want someone who has already internalized that.

Requirements

BS or higher in Aerospace, Aeronautical, Astronautical, or Mechanical Engineering
4+ years of aerodynamics, flight sciences, or aircraft design experience, ideally at a fast-moving UAS, defense-tech, or launch company
Hands-on CFD experience with demonstrated judgment about where fidelity is worth paying for and where it is not
Wind tunnel experience from planning through data reduction, on a real program
Strong scripting and tooling ability (Python, MATLAB, C++/Rust a plus) — you build your own analysis and visualization tools rather than waiting on someone else
Fluency with modern test data infrastructure and AI-assisted engineering workflows
Track record of taking an airframe or major configuration from concept through test and flight
Bias toward low-cost, manufacturable airframes: meeting the kinematic and packaging requirement with a simpler shape or cheaper fabrication route than the legacy answer
Willingness to work extended hours and occasional weekends around test campaigns and program milestones
Travel to test ranges and customer sites, including international travel

Nice To Haves

Prior work on tactical UAS, munitions, glide vehicles, or high-altitude platforms
Experience standing up a test data platform or flight test review process at a growing company
High-alpha, post-stall, or transonic aerodynamics experience, and the wind tunnel discipline to trust the numbers
GNC or 6-DOF plant model exposure — the airframe sets the kinematic ceiling and the plant model decides what's real; the team doesn't split those concerns across org charts
Prior flight test range experience, including international deployments

Responsibilities

Aerodynamic model and OML for ULR airframes: configuration, control surfaces, static margin, stability and control derivatives
The geometry-to-coefficient-table pipeline feeding 6-DOF simulation and flight software
CFD across the subsonic and transonic regimes (OpenFOAM, Ansys Fluent, STAR-CCM+, or equivalent), calibrated against low-fidelity methods (AVL, XFOIL/XFLR5, OpenVSP, Missile DATCOM) and test data
Wind tunnel campaigns end to end: test article definition, instrumentation plan, execution, data reduction, and the design changes that follow
Flight test support: pre-flight prediction, post-flight correlation, and closing the loop on the model
The flight sciences data and tooling stack — telemetry ingest, automated test review, visualization, and analysis tooling that lets the team go from test complete to decision in minutes, not days
Vehicle-level trades with propulsion, structures, and avionics, under real cost and manufacturability constraints for affordable-mass production