Software Engineer - Site Reliability Engineering

About Neo4j:

Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems. It includes enterprise-ready knowledge graphs for accurate, explainable, and governed AI; the most comprehensive, trusted, and easy-to-deploy graph capabilities across any environment and data source; and an unmatched ecosystem trusted by 84 of the Fortune 100 and supported by the world’s largest graph community. Intelligence that works. Results that matter.

Built to work everywhere and integrate with everything across every cloud for dynamic, personalized, and autonomous AI systems. We deliver quicker results, contextual knowledge, and solutions that impact customers and employees across the business.

Our Vision:

At Neo4j, we have always strived to help the world make sense of data.

As business, society and knowledge become increasingly connected, our technology promotes innovation by helping organizations to find and understand data relationships. We created, drive and lead the graph database category, and we’re disrupting how organizations leverage their data to innovate and stay competitive.

The Team

The Site Reliability Engineering team’s mission is to improve the reliability of Neo4j’s DBaaS product: Neo4j Aura. Operating at a global scale across all three major cloud providers, Aura runs hundreds of Kubernetes clusters and hosts thousands of Neo4j instances in production at any given time.

We’re reshaping what SRE means at Neo4j Aura—and we want you to be part of that journey.

Rather than firefighting or chasing alerts, we’re helping teams design for reliability from day one. That means building the tools, practices, and culture that embed SRE principles at the heart of how Aura operates. You’ll be joining a team focused on long-term resilience, engineering excellence, and meaningful collaboration with product teams.

The Role

• Automate for insight and scale: Build systems that make troubleshooting fast, safe, and scalable across thousands of Neo4j instances. From internal tools that surface clear insights to canaries that support safe rollouts, you’ll focus on automation that elevates reliability engineering.
• Treat operations as a software problem: Replace tribal knowledge and ad-hoc scripts with tools and systems that codify best practices—making operations predictable, scalable, and repeatable.
• Design for resilience, learn from failure: Own and evolve the tooling and processes behind incident response. From clear alerts to blameless reviews, you’ll help ensure teams respond with confidence and learn with clarity.
• Champion reliability as a product feature: Help teams define and act on SLIs and SLOs, turning reliability into a shared, data-driven priority across engineering.
• Create signals, not noise: Shape an observability stack that tells us what matters, when it matters—so