Who we are

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.

As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously.

We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.

The role

As the Lead Engineer for Low Observability Calculations, you will direct the high-fidelity Radar Cross Section (RCS) simulation workflow, from constructing complex analysis models to managing extensive sweep campaigns on high-performance computing clusters. Your primary objective is to generate critical signature data and hot-spot analyses to guide trade studies and shape the low-observable design of the airframe, antennas, and other key features. You will oversee all supplier activities for RCS calculation and testing, taking responsibility for the vital correlation of simulation results with physical measurement data to validate your models and ensure robust outcomes.

The day-to-day

Direct high-fidelity RCS simulations using MoM and MLFMM for airframe and payload-driven signature topics

Implement Physical Optics analyses for electrically large structures and fast-turn trade studies

Construct and maintain analysis models, managing CAD cleanup, material assignment, boundary conditions, and excitation setups

Create and optimise triangular surface meshes to ensure convergence and numerical stability

Conduct sweep campaigns across frequency, aspect, and polarisation to generate actionable deliverables including RCS polars and sensitivity studies

Diagnose and resolve solver issues such as convergence, mesh quality, and numerical artefacts

Guide signature-reduction trade studies collaboratively with structures and low-observability teams

Correlate simulation results against range and anechoic measurements, quantifying error bars and documenting assumptions

Optimise workflows for high-performance computing execution to automate result post-processing

Produce comprehensive program artefacts and clear, decision-ready reports for design reviews

Coordinate supplier activities for RCS calculation and testing

You should apply if you

Hold a degree in Aerospace Engineering, Electrical Engineering, Systems Engineering, or a related discipline

Have delivered computational electromagnetic and RCS analysis for complex aerospace platforms, including materials and radome modelling

Possess practical expertise with MoM/MLFMM and Physical Optics methods, demonstrating when to apply each

Are proficient in meshing and CAD-to-solver workflows, capable of diagnosing and resolving geometry-driven numerical problems

Can coordinate large sweeps on high-performance computing clusters, applying an understanding of solver scaling and convergence controls

Communicate complex results effectively to provide clear design guidance, hotspot attribution, and trade-offs

Nice to have

Understand extensions such as PTD, UTD, and edge diffraction methods

Note: We operate in an industry where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.

Join Helsing and work with world-leading experts in their fields

Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns

The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world