Aerodynamics Methodology and Software Engineer

Reposted 2 Days Ago
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Lausanne, Waadt, CHE
In-Office
Mid level
Artificial Intelligence • Computer Vision • Machine Learning • Robotics • Defense • Manufacturing
Building the Future of Autonomous Warfare. With Speed and Intelligence.
The Role
The Aerodynamics Methodology and Software Engineer will professionalize computational software, manage HPC/cloud infrastructure, and integrate automated workflows for UAV design optimization.
Summary Generated by Built In
About Us

Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.

Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.

Role

As an Aerodynamics Methodology & Software Engineer at Harmattan, you will bridge the gap between aerospace physics and high-performance software engineering. Your mission is to professionalize our internal computational ecosystem, manage our HPC/Cloud infrastructure, and transform research-grade scripts into production-ready engineering software. You will act as the lead architect for our agentic AI workflows, developing custom MCP servers and LLM-ready repositories to automate complex simulation loops and design optimisations. You are the engineer of the automated toolchains that allow our team to iterate on UAV designs with unprecedented speed and fidelity.

Responsibilities
  • Software Professionalization: Refactor research scripts and "specialist tools" into modular, high-performance, and maintainable Python/C++ libraries. Implement robust unit-testing and documentation standards. Make sure the team members follow the structure when developing code.

  • AI-Augmented Engineering & Orchestration: Architect agentic workflows and custom MCP (Model Context Protocol) servers to bridge LLMs with internal CFD solvers and databases; codify engineering tribal knowledge into SKILLS.md or CLAUDE.md files to enable AI-driven code refactoring, automated simulation setup, and intelligent data analysis.

  • MDAO Toolchain Integration: Architect a unified design environment by developing APIs and automated workflows that link disparate tools (e.g., OpenVSP, XFoil, and OpenFOAM) into seamless optimization loops.

  • Infrastructure & Scalability: Manage and optimize our calculation infrastructure, including Linux-based HPC clusters (Slurm) and/or Cloud computing (AWS/Azure).

  • Aero Database (ADB) Management: Design the data architecture for storing and retrieving high-dimensional aerodynamic results, ensuring the GNC and flight physics teams have "single-source-of-truth" access to vehicle performance data.

Requirements
  • Education: B.S., M.S., or Ph.D. in Aerospace Engineering, Computer Science, or Informatics with a proven track record in the aerospace sector.

  • Aerospace Background: Familiarity with the aerospace physics, data structures and I/O of industry tools such as OpenFOAM, ANSYS, XFOIL, OpenVSP, or QProp.

  • Advanced Programming: Expert proficiency in Python (NumPy, SciPy, Pandas) and ideally C++.

  • Modern AI & Agentic Systems: Proven ability to develop LLM-integrated tools and MCP servers that automate engineering tasks; experience maintaining "AI-ready" repositories using structured instruction files and building neural surrogate models to accelerate physical simulations.

  • DevOps & Infrastructure: Knowledge of Git/GitLab (CI/CD, Runners) and Linux/Unix environments. Experience with Bash scripting and Cloud-scale computing (AWS).

Nice-to-Have
  • Numerical Methods: Hands-on experience using CFD or other physical solvers. Able to select appropriate physics models (for example turbulence models), configuring numerical schemes, and fine-tuning solvers.

  • Machine Learning in Data Science: Knowledge in setting up surrogate models and tools for engineering practices (surrogate models)

We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

Skills Required

  • B.S., M.S., or Ph.D. in Aerospace Engineering, Computer Science, or Informatics
  • Expert proficiency in Python and ideally C++
  • Familiarity with aerospace physics and industry tools like OpenFOAM
  • Knowledge of Git/GitLab and Linux/Unix environments
  • Experience with Cloud-scale computing (AWS)

Harmattan AI Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Harmattan AI and has not been reviewed or approved by Harmattan AI.

  • Fair & Transparent Compensation Pay ranges are publicly shown for multiple U.S. roles (e.g., $140k–$200k base) and appear broadly in line with late‑stage startup/defense‑tech expectations based on the postings cited.
  • Equity Value & Accessibility Equity is repeatedly referenced in several job postings as part of total compensation, which can increase upside potential at a recently funded, high‑valuation company.
  • Strong & Reliable Incentives Sign‑on bonuses are explicitly mentioned in a hiring post for candidates who can start quickly, indicating the use of cash incentives in at least some hiring situations.

Harmattan AI Insights

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The Company
Paris, Île-de-France
131 Employees

What We Do

Harmattan AI is rising as a next-generation defense prime, building the future of autonomous warfare. We leverage AI-driven autonomy, real-time intelligence, and conflict-ready production to deliver attritable systems and autonomous mission management software. Designed for the real-world needs of warfighters, our solutions enable faster deployment, sharper decision-making, and battlefield dominance.

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