Senior Platform Engineer

At Arbor, we’re on a mission to transform the way schools work for the better. We believe in a future of work in schools where being challenged doesn’t mean being burnt out and overworked. Where data guides progress without overwhelming staff. And where everyone working in a school is reminded why they got into education every day.

Our MIS and school management tools are already making a difference in over 12,000 schools and trusts. Giving time and power back to staff, turning data into clear, actionable insights, and supporting happier working days.

At the heart of our brand is a recognition that the challenges schools face today aren’t just about efficiency, outputs, and productivity—but about creating happier working lives for the people who drive education every day: the staff. We want to make schools more joyful places to work, as well as learn.

About the Role

We are looking for an experienced and collaborative Senior Platform Engineer to join our Engineering team and help us take strong ownership of platform components and contribute to the design of robust, scalable, and secure systems. The remit and focus of the role is to work alongside the Platform Tech Lead and Engineering Manager to deliver high-quality engineering work, support fellow engineers, and help embed a culture of reliability and operational excellence. It’s a broad and exciting role, so we’re looking for someone up for a challenge—if you’re highly technical and a good team player, this is the role for you.

Core Responsibilities

• Architectural Contribution: Contribute to system design and architecture decisions, working with the Tech Lead to balance trade-offs between speed, scalability, maintainability, and security.
• Reliability and Performance: Take ownership of services from design through to production, ensuring they are observable and meet agreed Service Level Objectives (SLOs). Identify and deliver improvements in platform reliability, performance, and efficiency.
• Automation: Take an automation-first approach to improving automation across infrastructure and operations to reduce toil and increase the team's velocity.
• Technical Standards: Apply and uphold coding standards, write well-tested and reusable code, and engage with the architecture community to share best practices. Enable AI agents to act as force multipliers within our codebase. Ensure services meet production readiness standards.
• Planning and Delivery: Provide accurate estimates and feasibility input on technical work. Deliver work iteratively, contribute to release planning, and participate in post-release reviews. Raise dependencies within planned work.
• Mentorship: Support and mentor fellow engineers through code review, pairing, and constructive feedback. Share knowledge generously across the team.
• Incident Response: Participate in on-call rotations and incident response. Lead investigations, contribute to post-mortems, and drive follow-up improvements.
• Collaboration: Work closely with Product Managers, Engineering Managers, the Tech Lead, and other engineers to align technical delivery with product strategy. Communicate technical concepts clearly to both technical and non-technical stakeholders.

Requirements

• Experience: Considerable professional experience in Platform Engineering on complex, scalable systems.
• Cloud Systems: Strong hands-on expertise with AWS and distributed cloud architectures.
• Platform Scale: Experience operating platforms serving high request volumes in production with traffic of at least 6,000 req’s/sec. A deep understanding of enterprise deployment and maintenance processes such as blue-green deployments.
• Infrastructure as Code: Proficiency with Terraform and configuration management tools.
• Scripting: Strong skills in Python, Go, or a similar language for automation and tooling.
• Programming: Significant experience working in Java, C++/#, PHP, or another language; preferably in a sizable Object-Oriented codebase.
• Observability: Hands-on experience with monitoring and observability platforms (e.g., DataDog, Prometheus, or equivalent), and incident/problem management practices.
• System Design: Solid understanding of distributed systems, microservices, and resilience patterns.
• Containerisation: Hands-on experience with containerization and orchestration technologies (Docker, Kubernetes, ECS).
• CI/CD: Practical experience with building and maintaining CI/CD pipelines for automated deployments.
• Mentorship: Experience supporting and mentoring fellow engineers through code review, pairing, and feedback.
• AI and Productivity: Experience using agentic AI, or an interest in increasing productivity with new tooling including agentic AI.

Bonus Skills

• Experience with chaos engineering and reliability testing.
• Knowledge of security best practices and compliance frameworks.
• Contributions to open-source projects or the software community.
• Experience running ECS at scale.
• Experience working with (agentic and generative) AI to increase productivity.