Principal Engineer, AI Infrastructure (R4941)

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  • Shieldai
  • San Francisco, CA
  • Full-Time
  • 6 days ago
  • $320000 - $490000
Shieldai
Published
May 14, 2026
Location
San Francisco, CA
Job Type

Principal Engineer, AI Infrastructure (R4941): our view in 3 lines...

  • The Role: A senior engineer responsible for scaling and operating AI infrastructure that supports autonomy development across defense platforms.
  • The Person: Design and scale the AI and data platform used to train models, run simulations, manage data, evaluate models, and deploy optimized models into constrained operational environments.
  • Requirements: Experience training foundation models, running large-scale and multi-fidelity simulation, managing training data, evaluating models, and deploying optimized models to edge systems.

Job Description

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:

Shield AI builds autonomy systems for defense applications, including air, maritime, and space platforms operating in complex and contested environments.  

We are establishing a centralized AI and Data Platform organization responsible for the infrastructure that underpins autonomy development across Hivemind and other programs. This team owns the systems used to train models, run simulation, manage data, and deploy models to operational environments.  

We are seeking a Principal Engineer that will scale an initial architecture into a platform that supports multiple autonomy programs.  

Success in this role requires disciplined execution, delivering fast iteration for engineering teams while maintaining reliability, cost control, and architectural consistency as the system scales.  

The Principal Engineer is accountable for ensuring engineers can move efficiently from idea to trained model to deployed capability, and that infrastructure decisions reflect the realities of the domain, including simulation-driven development, continuously evolving multi-modal sensor data, and deployment to constrained and reliability-critical systems.  

This role spans the full lifecycle of autonomy development, training foundation models, running large-scale and multi-fidelity simulation, managing training data, evaluating models, and deploying optimized models to edge systems.  

A key part of this role is defining how these capabilities extend beyond internal use. This includes establishing how Shield AI delivers AI infrastructure in customer environments across on-premise, cloud, hybrid, and sovereign or nationally constrained environments.  

#LI-DM2
#LF
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.
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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. 
Key Skills
? Key Skills in dark blue have been inferred based on similar industry roles
Kubernetes Docker AWS GCP CUDA Pytorch Tensorflow Distributed Training CI/CD Model Deployment To Edge

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