Staff Software Development Engineer in Test, Cloud Applications

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.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock their abilities in orchestration with intelligent machines.

Position Overview:

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 at scale. The 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.

The ideal candidate combines strong software engineering skills in Python with deep expertise in distributed systems testing, cloud-native environments, mobile testing platforms, and data validation frameworks.

Essential Job Functions:

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

Education and/or Work Experience 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

Demonstrated experience designing and implementing automation frameworks or validation platforms across multiple layers of the stack (UI, API, service, integration, and data)

Strong experience validating web applications, APIs, and distributed microservices architectures

Demonstrated ability to integrate automated validation strategies into CI/CD pipelines

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

Things that make a difference:

Master’s degree in Computer S