Sr. Principal Gas Turbine Performance Engineer (San Diego, CA)

Solar Turbines•San Diego, CA

4d•$128,470 - $192,710•Onsite

About The Position

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Sr. Principal Gas Turbine Performance Engineer — AI‑Accelerated Engineering Why this role If you love the rigor of thermodynamics and the satisfaction of making models match reality—and you’re excited about using modern AI tools to amplify engineering impact—this role is built for you. You’ll sit at the crossroads of engine physics, product decisions, and real operating data, building performance models and software that influence everything from new product definition to test cell execution to fielded fleet operations. What the Performance Group does The Gas Turbine Performance Group leads concept and advanced cycle studies and delivers calibrated performance predictions for new and upgraded engines. We oversee performance during engine development, support production and acceptance testing, and enable product support teams worldwide with the tools needed to analyze, predict, and guarantee engine performance. A core part of our mission is building and maintaining the ecosystem (models, workflows, automation, and data pipelines) that turns thermodynamics + test + field data into decisions. Increasingly, our transient cycle models and calibrated physics tools are the foundation for AI‑enabled digital twins—unlocking longer service intervals, better cycle‑count capability, and improved efficiency through operational flexibility. What you will do Turn data into engineering decisions. Analyze acceptance test and fleet/field datasets to trend performance, troubleshoot issues, and monitor aeromechanical/operability behavior across product lines. Own high‑stakes performance predictions. Build, calibrate, and defend steady‑state and transient performance models for new products, upgrades, and investigations—where accuracy matters and assumptions must be explicit. Build the tools engineers rely on. Develop and maintain the internal software used across design, sales/applications, customer services, overhaul, and customer sites—improving usability, automation, traceability, and confidence in results. Accelerate engineering with AI. Apply modern AI techniques: speeding up calibration and uncertainty exploration, enabling anomaly detection and diagnostics, creating reduced‑order models that stay grounded in physics, supporting digital twin workflows using physics‑guided learning approaches. Collaborate across disciplines. Work shoulder‑to‑shoulder with design, controls, test, operations, and digital teams to solve urgent problems quickly while also building long‑term capability. What you’ll love about the work Physics-first engineering with direct line‑of‑sight to real hardware and customer outcomes. High leverage: your models and tools scale across programs, teams, and global sites. A modern toolchain mindset: automation, reproducibility, and AI‑assisted workflows are part of the job—not a side hobby.

Requirements

B.S. / B.Eng. in Mechanical or Aerospace Engineering (or closely related field) plus 8+ years applying thermodynamics and performance engineering to real-world problems.
Strong foundation in gas turbine performance and thermodynamics (cycles, maps, matching, operability concepts, off-design behavior).
Demonstrated ability to work through ambiguity, manage multiple priorities, and deliver high-quality results under schedule pressure.
Clear written and verbal communication—you can explain model assumptions, results, and risk to both technical and non-technical partners.
Proven habit of finishing work with thoroughness and reliability (validation, documentation, and follow-through).

Nice To Haves

M.S. (or equivalent experience) with a specialty in gas turbine performance, aerodynamics, or closely related area.
Deep experience with modeling, calibration, and troubleshooting of gas turbine performance/operability in steady state and/or transient.
Strong engineering software skills—building scripts, code, or automation that makes other engineers faster and improves quality.
Familiarity with controls and control logic (or willingness to partner closely with controls teams).
Tools & technologies (typical, not exhaustive) 1‑D / multiphysics engine performance tools (e.g., NPSS or similar) Programming/scripting: Python (strongly preferred), and/or C/C++/C#/Fortran/VBA Engineering computing: MATLAB / Simulink Analytics & visualization: Tableau (or similar), plus modern data tooling as applicable Standard productivity tools (Microsoft Office suite)

Responsibilities

Turn data into engineering decisions.
Analyze acceptance test and fleet/field datasets to trend performance, troubleshoot issues, and monitor aeromechanical/operability behavior across product lines.
Own high‑stakes performance predictions.
Build, calibrate, and defend steady‑state and transient performance models for new products, upgrades, and investigations—where accuracy matters and assumptions must be explicit.
Build the tools engineers rely on.
Develop and maintain the internal software used across design, sales/applications, customer services, overhaul, and customer sites—improving usability, automation, traceability, and confidence in results.
Accelerate engineering with AI.
Apply modern AI techniques: speeding up calibration and uncertainty exploration, enabling anomaly detection and diagnostics, creating reduced‑order models that stay grounded in physics, supporting digital twin workflows using physics‑guided learning approaches.
Collaborate across disciplines.
Work shoulder‑to‑shoulder with design, controls, test, operations, and digital teams to solve urgent problems quickly while also building long‑term capability.