Shield AI

Staff Engineer, Autonomy Factory Pipeline (R5276)

Shield AI$120K — $145K *
Aerospace & Defense
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience.
  • Proficiency in Python for data analysis and scripting, with familiarity in libraries like NumPy and Pandas.
  • Experience with automated testing systems, CI/CD processes, and container technologies like Docker and Kubernetes.
  • Solid grasp of software engineering practices including version control and debugging in Linux environments.
  • Knowledge of distributed computing or container orchestration is a plus.
  • Strong problem-solving abilities in complex software systems.
  • Must be able to obtain and maintain a U.S. SECRET security clearance.

Responsibilities

  • Develop and maintain Python-based data analysis pipelines for log data and performance metrics.
  • Create and debug C++ or Python test orchestration wrappers for HM Forge.
  • Implement scenario-generation and domain-randomization scripts for autonomy testing.
  • Analyze simulation logs and network captures to troubleshoot and debug software issues.
  • Utilize generative AI tools to enhance analysis suite development and maintenance.
  • Automate workflows for generating and evolving analysis suites and identifying testing needs.
  • Prototype distributed orchestration using Terraform and Kubernetes to support testing environments.

Benefits

  • Comprehensive benefits including bonus and equity options.
  • Full-time employee benefits package with access after 60 days for temporary employees.
Full Job Description
As a Software Engineer on the HMS Factory Team, you will develop, implement, and maintain the automated testing frameworks, log analysis tools, and scenario-generation scripts built on top of the Hivemind Platform (HMP) SDK. Your work is highly technical and hands-on, directly enabling hundreds of autonomy and systems developers to rapidly verify AI Pilot behaviors across our expansive portfolio set. In this role, you will navigate complex environment boundaries between secure GovCloud and commercial ecosystems, tackling deep build-system challenges such as dependency migrations and establishing reliable artifact and source-mirroring pipelines across isolated networks. You will write python-based analytics libraries, build custom wrappers around the HMP Forge test orchestrator, and programmatically generate complex testing environments using domain randomization. You will also participate in the hands-on prototyping and deployment of new distributed testing technologies like on top of the Forge Server to support massive batch-testing runs. Additionally, you will serve as a critical technical bridge, translating raw simulation telemetry into structured, high-fidelity insights while keeping mainline branches unified and stable in the face of varying program upgrade cadences. What you'll do: • Write, optimize, and maintain advanced Python-based data analysis pipelines and custom analyzers (such as the Shared Analysis Tool) to parse simulation runs, extract log data, and calculate mission performance metrics. • Develop, debug, and maintain custom C++ or Python adapters and automated test orchestration wrappers around core HM Forge to satisfy program-specific validation requirements. • Implement programmatic scenario-generation pipelines and write domain-randomization scripts to systematically test autonomy behaviors under highly varied environmental conditions. • Analyze simulation log files, rosbags, and network captures to isolate, reproduce, and debug autonomy software defects or simulator failures. • Leverage generative AI and agentic AI tooling to dramatically accelerate the development, refinement, and maintenance of analysis suites used to characterize performance and validate HMS solutions. • Build reusable agentic workflows that automate the generation and evolution of analysis suites, including automated discovery and interpretation of available test data and system outputs, intelligent identification of analysis needs, and development of new analyzers for HMS performance characterization and validation. • Build, test, and write Terraform or Kubernetes configuration files to prototype and deploy distributed orchestration templates on top of the Forge Server. • Write reusable, clear step-by-step developer guides, API documentation, and workspace templates to help program engineers implement automated simulation tests. • Design and evolve common telemetry ingestion, analysis, and reporting frameworks that enable consistent performance evaluation across HMS programs. Required qualifications: • Typically requires a Bachelor's degree in Computer Science, Computer Engineering, Aerospace Engineering, Systems Engineering, or related technical discipline, or equivalent practical experience. • Strong software development background in Python, particularly for data analysis, scripting, and automation tooling (utilizing libraries like NumPy, Pandas, or similar). • Hands-on experience with automated test orchestration, CI/CD, simulation environments, and container-based architectures (Docker, Kubernetes). • Solid software engineering fundamentals, including version control (Git), automated testing, and disciplined debugging practices in a Linux environment. • Familiarity with distributed compute frameworks or container orchestration tools is highly preferred. • Strong technical problem-solving skills, with the ability to troubleshoot complex, asynchronous software systems. • Ability to obtain and maintain an active U.S. SECRET security clearance (U.S. citizenship required). #LI-LD1 #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.

About Shield AI

Shield AI is a defense technology company that develops artificially intelligent systems for military applications. The company was founded in 2015 by Brandon Tseng, Ryan Tseng, and Andrew Reiter, and is headquartered in San Diego, California. Shield AI's products include autonomous drones and software that can be used for reconnaissance, surveillance, and other military operations. The company's mission is to reduce the number of military casualties by providing soldiers with better intelligence and situational awareness. Shield AI has received funding from a number of investors, including Andreessen Horowitz and Founders Fund.
Learn more about Shield AI
Size
200 employees
Industry
Founded
2015

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