An application made for this job — a tailored resume and cover letter that speak straight to the posting.
Defense Hardware Delivery seeks a senior aero engineer to own the aerodynamic model and outer mold line for ULR airframes, including the pipeline to coefficient tables for 6-DOF sims and flight software. You will drive CFD studies, wind tunnel campaigns, and flight-test correlation end-to-end on a fast-moving defense program.
You will also shape the flight sciences data stack, real-time telemetry, automated test orchestration, and AI-enabled analysis, embedding modern tooling from day one to
Client: Defense Hardware Delivery
Location: Herndon, VA (on-site) — Denver, CO considered for the right candidate
Reports to: VP of Aircraft Design / VP of Aircraft Programs
Type: Full-time
Base: Starting at $140,000, commensurate with experience, plus meaningful early-stage equity and bonus eligibility ranging up to $175,000
Clearance: U.S. Person required; ability to obtain and hold a security clearance
Our client builds a family of high-altitude balloon platforms, balloon-deployed ISR and communications buses, autonomous glide vehicles, and high-altitude dispensers alongside a family of ultra long range (ULR), affordable-mass, ground-launched one-way attack and ISR drones.
Our systems are flying and being tested in operationally relevant environments today, including active RF and flight test campaigns in Ukraine. We are small, moving fast, and every engineer here owns hardware that flies.
You will own the aerodynamic model and outer mold line for our ULR airframes: body shape, control surfaces, static margin, stability and control derivatives, and the pipeline that turns geometry into the coefficient tables that our 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 this company. We 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 into Aventra 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.
We 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 — we do not treat these as novelties. An engineer who leverages them well produces multiples of the design iterations of one who does not, and we want someone who has already internalized that.