Principal CFD Engineer

As a Principal Simulation Engineer (Delivery), you are a technical leader and problem solver who is passionate about creating practical, high-impact solutions that enable customers to make better engineering decisions. You combine deep simulation expertise with strong leadership and customer ownership, and you excel at working directly with customers (often directly on-site) to build CAE models that are integrated into AI-tools that are both useful and used.

You bring deep expertise in fluid mechanics, heat transfer, and multiphase modelling, with a solid ability to apply fundamental knowledge to real-world phenomena across a wide range of engineering applications. Highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent and adept at automating these tools to create scalable optimisation workflows that drive impactful results. Experience in parametric CAD modelling (NX or CATIA) and coding in Python/Java, (or the ability to quickly learn programming languages), is an advantage.

With 5+ years of industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re confident setting up CFD simulations independently, interpreting complex results with depth, and making informed decisions based on solid engineering judgement.

In this role, you’ll work closely with our Data Scientists, Machine Learning Engineers, and customers to understand and define the engineering challenges we are solving.

You’ll play a crucial role in delivering high-fidelity simulations by:

• Leading the technical direction and delivery of complex multi-physics simulation workstreams, remaining hands-on for the most challenging aspects while guiding teams through execution.


• Partner with customers to address their most complex engineering challenges through advanced CAE & AI solutions; present results clearly, recommend actionable next steps, and balance accuracy with efficiency under tight deadlines.


• Independently building and/or guiding others to develop complex multi-physics models from geometry clean-up and meshing, to simulating and post-processing complex real-world phenomena, integrating experimental data for model validation.


• Building robust parametric CAD models (NX or CATIA) coupled with simulation pipeline automation, for executing advanced design optimization and DoE studies.


• Working at the intersection of CAE and Data Science to generate high-quality simulation datasets for training Machine/Deep Learning models. Leveraging data sampling techniques to efficiently capture the design space, reduce computational cost, and enhance model accuracy.


• Accelerate high-fidelity modelling by using Flux (our cloud platform) and on-premise HPC resources, going beyond smart meshing and model setup to achieve real performance gains.


• Continuously improving engineering best practices, adapting CFD model setups and outputs to support the development of Deep Learning surrogates.


• Combining project leadership with a strong commitment to mentoring junior colleagues, contributing to a culture of collaboration, growth, and shared success.


• Traveling globally (North America, Europe, Asia, Oceania), on average 3-4 weeks per quarter, to work side-by-side with customers in building solutions on-site.

Please note, this role is based in New York, working 2-3 days per week in our Manhattan office.