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

Brain Corp

17h • $147,859 - $184,823 • Remote

About The Position

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

• 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 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
• 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
• 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 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
• 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
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree