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San Diego, California, United States
Onsite
The Hivemind Software Engineering Integration and Test team is seeking a Senior Automated Test Engineer to design, develop, and scale advanced automated testing and CI/CD infrastructure for our next-generation autonomy platform. You will help develop test frameworks that enable this software ecosystem to create, test and deploy resilient autonomy capabilities for unmanned aircraft and robotic platforms operating in complex, contested, and GPS-denied environments. You will work with a robust suite of autonomy and mission software components, including production flight code, simulation and synthetic environment tooling, mission planning and orchestration systems, operator-facing Ground Control Station (GCS) applications, telemetry and data pipelines, and cloud-native developer infrastructure.
In this role, you will help ensure the reliability, scalability, and quality of the Hivemind ecosystem through advanced automation, validation infrastructure, and AI-assisted engineering workflows. You will develop automated test frameworks, CI/CD systems, and verification tooling that support distributed autonomy software spanning onboard edge compute, APIs, web-based operator interfaces, simulation environments, and hardware-in-the-loop systems. Working closely with software, autonomy, simulation, and systems engineering teams, you will contribute to a high-assurance development environment focused on mission-critical reliability, rapid iteration, and engineering excellence. The ideal candidate has strong experience in Python-based automation, distributed systems testing, developer tooling, and modern CI/CD practices, along with an interest in autonomy, aerospace, robotics, or safety-critical software systems. Experience leveraging AI-assisted development and intelligent automation tools to accelerate testing, debugging, analytics, and developer productivity is highly valued.
Design, develop, and maintain automated test frameworks for Autonomy and UI applications.
Develop scalable automated test infrastructure for functional, integration, regression, system, and end-to-end testing across distributed software and hardware environments.
Create and maintain CI/CD pipelines in GitLab using YAML configurations and shell scripting to support automated build, test, and deployment workflows.
Build workflow automation tools and utilities in Python to improve test execution efficiency, reporting, environment setup, and developer productivity.
Develop and maintain UI and API test automation using Go and TypeScript for modern web-based operator interfaces and mission control applications.
Integrate automated testing into continuous integration environments to support rapid software delivery and high reliability standards.
Collaborate closely with software, autonomy, simulation, and systems engineering teams to define verification strategies and improve software quality throughout the development lifecycle.
Develop automated validation solutions for safety-critical and mission-critical aerospace software systems.
Create test harnesses, simulators, stubs, and mocks to support automated verification in both simulated and hardware-in-the-loop (HIL) environments.
Analyze test results, troubleshoot failures, and work with development teams to isolate root causes and improve system reliability.
Improve test coverage, execution speed, maintainability, and observability of automated test systems.
Contribute to software quality standards, coding best practices, and automation architecture decisions.
Maintain clear technical documentation for test frameworks, automation workflows, CI/CD infrastructure, and validation procedures.
Support release qualification activities and ensure traceability between requirements, tests, and verification results where applicable.
Represent the Integration and Test Role in design reviews and advocate for a culture of engineering excellence and continuous improvement.
Develop AI-assisted engineering workflows and analytics tools using modern coding agents such as Claude Code, Codex, and related LLM-based development platforms to improve test generation, failure triage, debugging, and developer productivity.
Design intelligent automation pipelines that leverage AI-assisted code generation, log analysis, test analysis, and workflow orchestration to accelerate software verification and validation processes.
Evaluate and integrate emerging AI-driven software engineering tools into automated test and CI/CD ecosystems while maintaining reliability, traceability, and engineering quality standards.
5+ years of experience building scalable, maintainable automation frameworks and/or developer tooling in Python.
5+ years of experience working with package management, dependency management, and build systems using tools such as conan, pip, setuptools, poetry, and nix or similar.
5+ years of experience building tooling for automated log collection, analytics, reporting, and failure triage.
Strong understanding of asynchronous and concurrent programming in Python for scalable automation and parallel test execution.
Experience developing and maintaining CI/CD pipelines using GitLab CI, YAML, and shell scripting.
Experience with automated testing of distributed systems, backend services, APIs, and web-based UIs.
Familiarity with modern test frameworks, automated validation strategies, and software quality methodologies.
Experience working in Linux-based development environments.
Strong debugging and problem-solving skills in complex software systems.
Excellent collaboration and communication skills in cross-functional engineering environments.
Experience integrating Python with native C/C++ libraries and applications using bindings, wrappers, subprocess interfaces, or interoperability tooling.
Proficiency with Go and/or TypeScript for automation tooling or UI test development.
Experience with C++ development or testing.
Aerospace, robotics, autonomy, or safety-critical software experience.
Familiarity with simulation, hardware-in-the-loop (HIL), or embedded system testing.