Quality Engineer (SDET)

1 month ago

Remote, United KingdomMid Level

Responsibilities

Design, implement, and maintain automated integration- and API-level tests across distributed services.
Develop tests for asynchronous and event-driven workflows, including messaging, retries, ordering, and failure scenarios.
Contribute production-quality code to shared automation frameworks and quality tooling.
Design and execute performance and scalability tests, including realistic workloads, concurrency, and message throughput.
Integrate functional and performance tests into CI/CD pipelines and quality gates.
Support staging validation as the primary platform integration and quality assurance layer.
Analyze functional, integration, and performance results to identify systemic platform risks.
Partner with Product Owners and engineering teams to prepare targeted integration and performance tests for upcoming changes.
Collaborate with architecture, platform, and engineering teams to improve testability, reliability, and observability.
Use AI-assisted engineering tools to accelerate test creation, improve coverage, analyze failures, and reduce test flakiness.

Demonstrable experience with platform- or enterprise-scale SaaS quality assurance across distributed systems.
Strong coding ability in one or more of C#, TypeScript, or Python.
Experience designing and maintaining automated integration and API tests for distributed, cloud-native systems.
Understanding of cloud-native architectures, messaging, asynchronous processing, retries, ordering, and failure handling.
Hands-on experience testing event-driven systems with technologies such as Azure Service Bus, Kafka, SNS, or SQS.
Hands-on experience with performance testing tools and approaches such as k6, JMeter, or Gatling.
Experience designing performance scenarios and representative test data for load, concurrency, and message-driven workloads.
Experience integrating functional and performance testing into CI/CD pipelines; Azure DevOps is preferred.
Experience diagnosing complex system failures using logs, telemetry, and test data.
Hands-on experience with AI-assisted engineering tools for productivity, test quality, or failure analysis.
Bachelor’s degree in Computer Science, Software Engineering, or a related technical discipline, or equivalent practical experience.
Relevant certifications in cloud platforms, performance testing, or quality engineering are beneficial but not required.

201-500 employees