Manager, Simulation Engineering (R4870) V-BAT Division V-BAT Engineering - Software Dallas, Texas Dallas, Texas Full Time Employee 160000 - 240000 Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. Job Description: As the VBAT Simulation Lead, you will be responsible for improving and scaling our simulation capabilities for the V-BAT and future aircraft. You will design, resource, manage, build and integrate tooling across our various engineering teams (e.g. Aerodynamics, GNC, Propulsion, etc.) to enable efficient and scalable simulation workflows. Your simulation solutions will be a key development tool for other engineers and also a critical gate in our release process. Job Description: As the VBAT Simulation Lead, you will be responsible for improving and scaling our simulation capabilities for the V-BAT and future aircraft. You will design, resource, manage, build and integrate tooling across our various engineering teams (e.g. Aerodynamics, GNC, Propulsion, etc.) to enable efficient and scalable simulation workflows. Your simulation solutions will be a key development tool for other engineers and also a critical gate in our release process. #LI-SM1 #LD Full-time regular employee offer package: Pay within range listed + Bonus + Benefits + Equity Temporary employee offer package: Pay within range listed above + temporary benefits package (applicable after 60 days of employment) Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information. ### Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. What you'll do:

Work with tech leads and stockholders to design, track, and report simulation roadmaps and release plans.

Align needs and priorities across many teams and disciplines

Hire and manage a team of specialized simulation engineers across multiple locations.

Collaborate with cross-functional teams, including software engineers, autonomy engineers, and aerodynamics engineers, to ensure the simulation accurately reflects real-world conditions

Create and maintain processes and workflows to build confidence in simulation tooling to both internal and external customers.

Stay updated with the latest advancements in simulation technologies and drive best practices across the team

Build and maintain documentation and dashboards to quickly provide data and status to leadership.

Required qualifications:

BS in Computer Science or related engineering field with 8+ years of professional experience.

3+ years of experience leading engineering teams or projects.

Passion for simulation and testing with the goal of ensuring safety and reliability at scale.

A proven track record of working with multiple stakeholder groups and managing clear and successful roadmaps

Strong foundation in C++ and software architecture

Foundational knowledge of statistics and its application in software development, testing, and data analysis.

Solid understanding of mathematics (especially linear algebra) and foundational physics, with the ability to interpret technical papers and algorithms effectively.

Preferred qualifications:

Experience with Docker, Kubernetes, and/or containerized application development

Familiarity with rigid body dynamics (e.g. Euler’s equations, quaternions), aerodynamics, propulsion systems, etc.

Experience with Python 3 and data science frameworks (e.g. NumPy, Pandas, Dagster)

Experience with robotics concepts, including node-based architectures such as ROS or similar middleware frameworks.

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