Senior Operational Performance Engineer, Performance Tracking & Evidence Strategy

Job description

Job responsibilities

• Own vehicle-level performance tracking from conceptual design through production, maintaining a continuous picture of predicted performance, measured performance, and the deltas between them as the vehicle matures.
• Own vehicle-level uncertainty tracking, quantifying confidence in each performance claim, prioritizing the highest-consequence unknowns, and driving them toward closure.
• Lead vehicle performance assessment and evidence planning across the development lifecycle, scaling rigor from early demonstrators through production commitments.
• Translate performance objectives, requirements, and engineering risks into analysis plans, measurement requirements, data quality needs, and success criteria.
• Define what must be measured, under what conditions, and to what confidence to produce the required evidence, and recommend tests to Flight Test and discipline teams accordingly.
• Establish pre-test predictions and uncertainty expectations, then assess ground and flight test results against those benchmarks to determine what has been learned and what remains open.
• Partner with Flight Test and discipline teams to make data requirements practical and achievable, explaining engineering intent and prioritizing needs.
• Partner with MDAO and Conceptual Design to feed model correlation results, validated data, and prediction-accuracy trends back into design and sizing tools, improving fidelity and reducing uncertainty on future vehicles.

Job requirements

• Bachelor's degree in Aerospace Engineering, Mechanical Engineering, or a related technical field.
• 5+ years of experience in aerospace vehicle performance assessment, flight test analysis, test engineering, experimental engineering, or a closely related discipline.
• Demonstrated ownership of performance tracking, evidence strategy, or model correlation for complex aerospace vehicles or physical systems.
• Experience maintaining a vehicle- or system-level performance picture over time, including tracking predicted-versus-measured deltas and confidence as a design matures.
• Strong understanding of vehicle performance and the interactions among mass properties, aerodynamics, propulsion, structures, power, controls, and vehicle configuration.
• Experience assessing experimental, ground test, or flight test data against performance predictions or engineering models.
• Experience using Python, Julia, MATLAB, or similar tools for technical analysis and data processing.
• Proven ability to influence cross-functional teams and collaborate effectively across engineering disciplines.