Staff Software Development Engineer in Test, Cloud Applications (Remote)

About the role

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 SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Responsibilities

• Automation Platform Development
• 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
• Mobile Platform Validation
• Architect automated testing strategies for mobile applications across iOS and Android platforms
• Leverage cloud device platforms such as BrowserStack 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
• Cloud & Distributed Systems Validation
• 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 DevOps teams to embed quality gates within deployment pipelines
• Drive improvements in system reliability, performance, and resilience testing
• Data Platform Quality Engineering
• 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
• Technical Leadership & Engineering Influence
• 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 DevOps teams to align testing strategies with product goals
• Facilitate the adoption of AI/ML/LLM-enabled testing strategies where appropriate
• Contribute to system and design reviews to ensure new components are observable, testable, and resilient
• Shape the direction of the Quality Engineering discipline, driving adoption of modern testing approaches and tooling workflows
• Working Lead & Team Leadership
• Serve as a working lead and manager for a team of SDETs, providing architectural guidance and mentorship
• Conduct performance reviews, support career development, and foster engineering excellence within the team
• Guide the team’s technical direction while remaining hands-on in framework design and automation architecture
• Coordinate quality engineering initiatives across projects to ensure alignment with organizational priorities
• Data-Driven Quality Insights
• Establish metrics, dashboards, and observability strategies that provide real-time visibility into product health and release readiness
• Provide engineering leadership with data-driven insights into system reliability, defect trends, and risk areas
• Investigate system behaviors and diagnostic data to identify root causes and drive cross-team issue resolution
• Ensure traceability between requirements, implementation, and verification

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience
• 7+ years of experience in software engineering or SDET roles working with complex distributed systems, with at least 3 years in a technical leadership role
• Strong software development skills in Python, including building automation, tooling, or validation systems
• Strong experience validating web applications, APIs, and distributed microservices architectures
• Strong understanding of modern software testing methodologies and quality engineering practices, including functional, integration, and system testing
• Experience implementing browser automation frameworks such as Playwright or Cypress
• Strong debugging and analytical skills, including the ability to investigate complex failures and support root cause analysis
• Demonstrated ability to mentor engineers and influence engineering practices within a team or product area
• Excellent communication, collaboration, and technical documentation skills
• Proven capability in utilizing AI/ML-assisted testing techniques to enhance coverage, diagnostics, and defect detection

Preferred Qualifications

• Experience validating data platforms and data pipelines, including SQL-based systems, data warehouses, and ETL/ELT workflows
• Experience implementing contract testing or service-level validation strategies in distributed systems
• Experience building or improving quality dashboards, metrics, or reporting systems used to evaluate system health and release readiness
• Experience testing mobile applications and working with cross-device testing platforms
• Experience in mobile robotics or industrial automation is a plus
• Experience with common sensors used in robotics, including cameras (RGB and Depth), LIDARs, IMUs and Sonars