Platform Quality Engineer

Role

Platform Quality Engineer is a hands‑on engineering role within Star Compliance’s centralised Platform Quality Engineering function, responsible for ensuring platform‑level quality assurance across the enterprise SaaS platform.

Reporting to the Lead Quality Architect, the Platform Quality Engineer contributes directly to the design, implementation, and maintenance of automated quality controls that validate cross‑service integration, core enterprise user journeys, and non‑functional platform characteristics. The role is focused primarily on integration and API‑level testing across a distributed, cloud‑native system, including asynchronous and event‑driven workflows.

Star Compliance’s enterprise platform is built on distributed services and cloud infrastructure, including messaging and integration components such as Azure Service Bus. The Platform Quality Engineer is expected to understand how these systems behave under load, failure, and recovery conditions, and how to test them to ensure reliability, resilience, and performance at scale.

The role places strong emphasis on validating failure modes, resilience, and recovery behaviour across distributed services, diagnosing complex system failures using logs, telemetry, and test data, and contributing to enterprise performance testing. The Platform Quality Engineer works closely with Product Owners and engineering teams to understand upcoming platform changes and integrations, ensuring the enterprise platform is validated under realistic functional and load scenarios ahead of release.

• Design, implement, and maintain automated tests primarily at the integration and API layers to validate behaviour across distributed services.
• Develop tests that validate asynchronous and event‑driven workflows, including messaging, retries, ordering, and failure scenarios (e.g., Azure Service Bus–based integrations).
• Contribute production‑quality code to shared automation frameworks and quality tooling used across the enterprise platform.
• Design and execute performance and scalability tests for the enterprise SaaS platform.
• Build and maintain performance test data, scenarios, and workloads that reflect real‑world usage patterns, including message throughput and concurrency.
• Integrate automated functional and performance tests into CI/CD pipelines, contributing to reliable, high‑signal quality gates.
• Support validation activities within the staging environment as the primary platform integration and quality assurance layer.
• Analyse functional, integration, and performance test results to identify systemic platform risks and improvement opportunities.
• Partner with Product Owners to understand upcoming platform changes and integrations, preparing targeted integration and performance tests in advance.
• Collaborate with architecture, platform, and engineering teams to improve system testability, reliability, and observability.
• Apply AI‑assisted engineering tools to accelerate test creation, improve coverage, analyse failures, and reduce test flakiness.
• Adhere to and contribute to quality standards, patterns, and engineering practices defined by the centralised Platform Quality Engineering function.

• Demonstrable experience in platform‑ or enterprise‑scale SaaS application quality assurance, with a focus on validating integration, non‑functional characteristics, and release readiness across distributed systems.
• Strong coding skills in one or more of C#, Type Script, or Python, with the ability to write clean, maintainable, production‑quality code.
• Demonstrated experience designing and maintaining automated tests at the integration and API layers for distributed, cloud‑native systems.
• Solid understanding of cloud‑native architectures and how to test them, including messaging, asynchronous processing, retries, ordering, and failure handling.
• Hands‑on experience testing event‑driven systems using cloud messaging or integration technologies (e.g., Azure Service Bus, Kafka, SNS/SQS, or similar).
• Strong hands‑on experience with performance testing tools and approaches (e.g., k6, JMeter, Gatling, or similar).
• Experience designing realistic performance test…