Platform QA & Test Infrastructure Engineer

73 Strings; Greater London; On-site; GBP 70,000 - 95,000; Full time

Job summary

73 Strings in London is seeking a QA and Test Infrastructure Engineer to build the testing platform across Java, Python, and TypeScript services. You will own test frameworks, CI pipelines, ephemeral environments, and contract testing to ensure reliable production deployments.

You will collaborate with Platform Engineering, SRE, and AI teams to design scalable test data, AI-enabled testing approaches, and robust evaluation methods while maintaining fast feedback for product teams.

Qualifications

• Hands-on engineering experience building test infrastructure, automation frameworks, or developer tooling.
• Strong programming ability in at least one of Python, Java, or TypeScript, and comfort reading all three.
• Experience owning test automation in CI/CD, including making a slow, flaky suite fast and trustworthy.
• Working knowledge of Kubernetes and containers to build and debug ephemeral environments.

Responsibilities

• Build and own test frameworks and harnesses used across services written in Java, Python, and TypeScript.
• Own test execution in CI: parallelisation, sharding, caching, selective test runs, fast feedback loop.
• Own ephemeral test environments per pull request on Kubernetes.
• Build contract testing between services to surface integration issues early.
• Own end-to-end and UI test infrastructure (Playwright, Cypress, or similar).
• Develop performance and load testing capabilities to catch latency issues.

Skills

Test automation

CI/CD

Python/Java/TS

Kubernetes

Data management

FinTech knowledge

Communication

Tools

Playwright

Cypress

Job description

73 Strings in London is seeking a QA and Test Infrastructure Engineer to build the testing platform across Java, Python, and TypeScript services. You will own test frameworks, CI pipelines, ephemeral environments, and contract testing to ensure reliable production deployments.

You will collaborate with Platform Engineering, SRE, and AI teams to design scalable test data, AI-enabled testing approaches, and robust evaluation methods while maintaining fast feedback for product teams.