Principal Platform Engineer

New

CazooAutomotive retail

Remote, UK basedFull-TimePrincipal

Salary not disclosed

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Job Details

Bring extensive backend or platform engineering experience building and operating high-traffic, business-critical systems.
Have strong cloud engineering expertise, preferably with Azure, and understand cloud-native architecture, managed services and infrastructure as code.
Be proficient in a modern backend language, ideally TypeScript/Node.js; experienced engineers with transferable backgrounds such as Java are also considered.
Have experience with distributed and event-driven systems, including technologies such as Kafka, Azure Event Hubs or Service Bus.
Have a solid understanding of Kubernetes, Docker, Terraform, CI/CD and observability tooling.
Have experience designing data-intensive services using relational and non-relational databases, caching and search technologies.
Demonstrate technical leadership through architectural influence, mentoring and driving complex initiatives across multiple teams.
Use sound engineering judgment to balance technical debt, delivery priorities and build-versus-buy decisions.
Be familiar with AI-assisted development tools such as Claude Code, Cursor or GitHub Copilot and understand their benefits and limitations.
Experience in automotive, marketplaces, classifieds or other consumer-facing digital platforms is advantageous.

Lead the design and delivery of cloud-native, event-driven services, including the safe retirement of legacy systems.
Own and deliver the roadmap for core platform capabilities, aligning priorities with Engineering, Product and Commercial stakeholders.
Write production code, review pull requests, solve complex technical problems and work alongside engineering teams.
Build and evolve shared services, tooling and engineering practices to improve developer experience.
Improve scalability, reliability, observability and operational standards across the platform.
Work with architects, Principal Engineers and cross-functional squads to turn architectural vision into practical solutions.
Mentor engineers, share knowledge and establish consistent engineering standards across teams.
Establish practices and guardrails for using AI development tools while maintaining quality and security.

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