Software Engineer II (Postprocessing)

What You'll Do

• Develop, test, debug, and maintain assigned CAE post-processing capabilities for engineering simulation products, with attention to result accuracy, performance, robustness, usability, and maintainability. • Contribute to solver result reading, result case management, contour plots, XY plotting, animation, result probing, min/max extraction, derived result calculations, result comparison, and report generation. • Implement and validate support for scalar, vector, tensor, transient, modal, frequency-domain, and load-step-based result data with guidance from experienced team members. • Participate in design discussions, code reviews, debugging, performance analysis, testing, and implementation planning for assigned components. • Investigate and resolve well-defined result interpretation issues, plotting errors, result synchronization problems, solver output discrepancies, performance bottlenecks, and customer-reported defects, escalating complex issues as appropriate.
• Required Qualifications Education • Bachelor’s or Master’s degree in Computer Science, Mechanical Engineering, Computational Engineering, Computer-Aided Engineering, Applied Mathematics, or a related engineering discipline.
• Experience • Bachelor’s degree with approximately 2–4 years of relevant software engineering experience, or a relevant master’s degree with little to no professional experience. • Foundational understanding of software development principles, data structures, algorithms, object-oriented design, debugging, testing, and maintainable code. • Academic, internship, research, or professional exposure to CAE, simulation, scientific computing, engineering data processing, visualization, or related technical domains. • Familiarity with CAE post-processing concepts such as result cases, contouring, XY plotting, animation, result probing, scalar/vector/tensor data, coordinate systems, units, or result transformations is desirable. • Programming experience in C++ gained through coursework, research, internships, personal projects, or professional software development. • Ability to implement well-defined software components, write unit or regression tests, diagnose defects, and learn an established production codebase with guidance. • Exposure to solver output formats, transient or frequency-domain results, numerical methods, visualization, or data-intensive applications is a plus. • Experience with CAE products or simulation platforms such as MSC Apex, Patran, Adams, Nastran, Marc, Abaqus, ANSYS, HyperWorks, ParaView, Tecplot, or equivalent technologies is preferred but not required. • Familiarity with AI-assisted software development tools such as GitHub Copilot, Cursor, or similar tools for coding, review, documentation, or engineering workflows is preferred.
• Technical Skills • Working proficiency in C++ and a sound understanding of object-oriented programming, data structures, algorithms, memory management, and modern software development practices. • Basic knowledge of CAE result concepts, including result cases, load steps, time steps, modes, scalar/vector/tensor quantities, coordinate systems, units, transformations, averaging, extrapolation, or derived results. • Academic, project, internship, or professional experience with one or more post-processing features such as contouring, XY plotting, animation, result probing, min/max extraction, result comparison, report generation, or automated validation. • Exposure to visualization frameworks or technologies such as VTK, OGRE, OpenGL, ParaView, Tecplot, Qt graphics/view frameworks, or equivalent technologies is preferred. • Development experience on Windows or Linux through coursework, research, internships, personal projects, or professional work; familiarity with build systems and source control is expected. • Ability to use debuggers, logs, stack traces, tests, and diagnostic tools to investigate software defects; exposure to Visual Studio Debugger, GDB, LLDB, or similar tools is beneficial. • Familiarity with automated testing and scripting, preferably Python, for regression testing, numerical validation, solver result comparison, benchmark models, or related engineering workflows.
• Soft Skills • Strong communication and collaboration skills. • Problem-solving and analytical thinking. • Ability to work independently and in a team environment. • Strong organizational and time-management skills.N/A We’re doing work that matters.
• Help us solve what others can’t.