Staff Software Developer in Test, Cloud Applications

Brain Corp•San Diego, CA

22h•Onsite

About The Position

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. 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.

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.

Nice To Haves

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.
Master’s degree in Computer Science, CE, EE.
Experience validating machine learning systems or ML-enabled applications, including model inference services, training data pipelines, or model output validation.
Experience with simulation-based testing environments, such as NVIDIA Isaac Sim or similar robotics simulation platforms.
Experience working in environments that combine cloud services, mobile applications, and data 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 is a plus.

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

Benefits

A discretionary annual target bonus
Stock options
401(k) plan with match (no waiting period and immediate vesting)
Comprehensive suite of insurance benefits for employees (and their families) to include a variety of medical plan options (including an HSA with employer contribution), dental, vision, life and disability insurance, Employee Assistance Program (EAP), Legal/Identity support plans, pet insurance.
Access to Flexible Spending Accounts (Medical and Dependent Care)
Generous paid time off including flexible vacation, Paid Sick Leave, time off for volunteering in the community, 10 paid company holidays, and a winter company shutdown
Daily on-site lunch available in the San Diego office
On-campus gym including pool and tennis courts in the San Diego office
Opportunities to connect with colleagues including monthly game nights, hikes, wellness challenges, and community events
Internal continuous learning events
Opportunities to share your own interests and hobbies with the Company