Senior Software Engineer in Quality Engineering

ABOUT SOTHEBY'S Established in 1744, Sotheby’s is the world’s premier destination for art and luxury. Sotheby’s promotes access to and ownership of exceptional art and luxury objects through auctions and buy‑now channels including private sales, e‑commerce and retail. Our trusted global marketplace is supported by an industry‑leading technology platform and a network of specialists spanning 40 countries and 70 categories which include Contemporary Art, Modern and Impressionist Art, Old Masters, Chinese Works of Art, Jewelry, Watches, Wine and Spirits, and Design, as well as collectible cars and real estate. Sotheby’s believes in the transformative power of art and culture and is committed to making our industries more inclusive, sustainable and collaborative.

THE ROLE We are seeking a Senior Software Engineer in Quality Engineering who will serve as a technical lead and innovator for our quality engineering efforts with proactive and solution oriented initiatives. This role is a greenfield opportunity – you will have the chance to shape quality strategy from the ground up and make a significant impact on our engineering culture and product excellence. You will build and maintain CI/CD test pipelines, strengthen service testability, and help teams diagnose hard‑to‑reproduce issues using logs, traces, and other technical evidence. The ideal candidate is someone who asks great questions while learning quickly, finds creative technical and process solutions to testing challenges, and has a proven record of driving improvements with modern AI tools.

RESPONSIBILITIES

• Lead cross‑team quality engineering initiatives in partnership with QA, Engineering Managers, and developers, with primary focus on back‑end services.
• Define and drive automation strategy and standards (framework design, maintainability, reliability), raising the quality bar across teams.
• Guide tooling decisions for service automation, including API testing, contract validation, test data and AI tools approaches.
• Build and evolve GraphQL and REST back‑end automation capabilities for microservices and event‑driven workflows, emphasizing service reliability and data integrity.
• Improve CI/CD validation by strengthening service‑level test pipelines, environment readiness, and dependable test data setup.
• Diagnose and reduce back‑end quality risks by targeting distributed‑system failure modes such as race conditions and consistency issues.
• Mentor QA engineers on service testing patterns, debugging approach, and practical automation design.
• Partner with developers on triage and root‑cause analysis using logs, traces, and request/response evidence.

The ideal candidate demonstrates strong ownership of their growth, actively learning new technologies and patterns as needed to improve quality outcomes.

REQUIRED EXPERIENCE & COMPETENCIES

• Bachelor’s degree in computer science/engineering or equivalent technical experience.
• 5+ years of software engineering experience, including automation across functional, end‑to‑end, regression, quality monitoring and performance testing for web‑based, microservices systems.
• Strong programming fundamentals with the ability to work across languages; experience with TypeScript and Go is required.
• Deep back‑end automation experience, including GraphQL API testing (required) and working knowledge of REST and SQL‑based validation.
• Ability to innovate, design and maintain scalable automation frameworks, including service‑level tests and test data strategy.
• Hands‑on experience building automation into CI/CD and managing quality gates using tools such as GitHub Actions (Bazel familiarity is a plus).
• Experience with API tooling (for example Postman‑style tools) and cloud testing platforms (BrowserStack/LambdaTest); Appium experience for mobile testing is required.
• Working knowledge of cloud/container environments (Docker, Kubernetes) and comfort troubleshooting distributed systems using logs and service‑to‑service signals.
• Strong analytical and leadership skills with a track record of influencing cross‑functional teams and communicating technical risk clearly.
• Demonstrated documentation skills for engineering‑facing standards and workflows (for example API/service testing standards).
• Practical experience using AI‑assisted development tools to accelerate automation delivery while maintaining quality, readability, and maintainability.
• Awareness of network and security fundamentals relevant to back‑end testing (authentication/authorization, headers, tokens, and common failure modes).
• Adaptable, self‑driven, and motivated to learn new technologies and domains quickly in a fast‑paced, distributed environment.