Software Development Engineer in Test, Cloud

Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more.

Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the Soft Bank Vision Fund, Clearbridge, and Qualcomm Ventures.

We are seeking a Staff Software Development Engineer in Test - Cloud Applications to lead the design and evolution of quality engineering architecture across our web applications, cloud services, mobile platforms, and data systems.

This role combines deep technical leadership with hands‑on engineering, operating as a working lead responsible for both architectural quality initiatives and the mentorship and management of a team of SDETs. The Staff SDET will guide a small team of engineers while remaining actively involved in designing and building scalable automation frameworks and validation platforms.

The role focuses on building engineering‑grade automation, quality platforms, and validation strategies that enable teams to deliver reliable systems  Staff SDET acts as a quality architect, partnering with engineering, platform, and product teams to embed validation directly into system design, CI/CD pipelines, and data workflows.

• Design and implement scalable automation frameworks and validation platforms using Python
• Build reusable automation libraries and developer‑facing tooling that enable teams to validate functionality earlier in the development cycle
• Architect automated validation strategies across:
  • Modern web applications
  • APIs and microservices
  • Distributed cloud systems
  • Mobile platforms
  • Data pipelines and analytics platforms including ML outputs
• Integrate automation frameworks into CI/CD pipelines to enable rapid feedback and high‑confidence releases

• Architect automated testing strategies for mobile applications across iOS and Android platforms
• Leverage cloud device platforms such as Browser Stack to enable scalable cross‑device testing
• Integrate mobile automation into CI/CD pipelines to support validation across devices, operating systems, and configurations
• Define strategies for mobile UI testing, API validation, and end‑to‑end workflow testing

• Design validation strategies for cloud‑native microservices architectures
• Enable automated testing for service interactions through contract testing, integration validation, and environment simulation
• Partner with infrastructure and Dev Ops teams to embed quality gates within deployment pipelines
• Drive improvements in system reliability, performance, and resilience testing

• Architect automated validation for data pipelines, data transformations, and data platform services
• Establish frameworks to validate data integrity, schema evolution, lineage, and reproducibility
• Partner with Data Engineering teams to ensure quality is built into analytics and machine learning
• Partner with data science and ML Ops teams to ensure reproducibility, monitoring, and validation of ML models within production systems, including drift detection and model performance validation

• Act as a technical leader across engineering teams, influencing architecture and engineering practices to improve product quality and system reliability
• Collaborate with product management, development, and Dev Ops teams to align testing strategies with product goals
• Facilitate the adoption of AI/ML/LLM‑enabled testing…