Software Engineer - Developer Experience

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 Neo4j’s managed cloud offering, Aura, brings the power of graph databases to the cloud. We’re forming a new team - Aura DevEx, and are looking for an ambitious Engineer to help build it. Aura DevEx is an enabling team for the Aura SaaS and cloud platform and works to improve and simplify onboarding and use of the Aura platform. Our DB software is developed to be delivered both on-prem and to our SaaS offering and Aura DexEx will play a vital role in bridging development of the DB in our cloud environment. We make Aura usable for them — in person, in docs, in CLIs, and through AI. We also work on things coupled to the AI domain for Aura development: agent skill files, AI instructions, and the workflows that let humans and agents work in this repository safely and well. The mix that matters here is software engineering, developer experience, and practical AI — not platform engineering as a full-time job. The Role Make Aura the place where the rest of Neo4j can build. Aura is a powerful environment, but a challenging one to enter. Aura DevEx exists so that “develop in Aura” is a product, not a tribal knowledge problem. You will work with all users of the platform - both avid users and people new to the platform. You’ll also work alongside teams to help them build on top of the platform. Between directly helping engineers you will take your learnings from the hands-on sessions and improve tooling and documentation or submit feedback to owning teams on how their devex could be improved. You will not own the delivery platform. You will partner closely with our Software Delivery team so the paved road stays the paved road, and with our platform teams to ensure engineers are empowered to extend the platform to meet their needs. What You'll Do Help teams outside Aura develop in Aura:

• Meet Neo4j Database (non-Aura) engineers where they are. Reduce the Aura-specific overhead of getting a change built, tested, and running in a dev environment.
• Improve the workflows, docs, and tooling that engineers need, — whether they are people who care about the database, a single service, or an integration, rather than the whole platform.
• Support incubation and onboarding: help teams become productive in Aura without Aura DevEx owning their product.
• Work with Software Delivery when the right fix is on the paved road, and take the work that is about who is developing and how they get started.
• Give feedback to the various platform teams to ensure that the underlying platform is intuitive, pleasant to use, and extensible.

Contribute to the AI domain for Aura development

• Maintain and evolve skill files and agent instructions (AGENTS.md, Cursor/Claude skills, and similar) so AI coding agents can operate in Aura with the same constraints we expect of humans.
• Put evaluation and feedback around AI workflows — quality, cost, failure modes, and whether they actually save engineers time.
• Help Aura and non-Aura teams adopt AI in their development process without each team inventing its own stack.

Treat DevEx as a product

• Work closely with internal engineers (Aura and non-Aura) to identify pain points.
• Make the experience as positive as possible for someone who does not already know Aura.
• Observe how people and agents use the skills, docs, and tools you ship, and iterate on that evidence.

What You’ll Need

• Strong collaboration and communication skills.
• Golang experience
• Experience using Golang for multiple software projects ranging from scripting to larger microservice-type applications.
• Some knowledge around the Golang build and packaging system.
• Solid software engineering experience, including shipping tools other engineers use (CLIs, libraries, internal platforms, or developer-facing services).
• Enough Kubernetes and container literacy to help someone develop in Aura — Pods, Deployments, Docker images, and how software gets onto a cluster. Deep operator/control-plane work is not the job; being lost in Kubernetes is not viable either.
• Experience with modern CI/CD and Git-based workflows: taking a change from a branch to something running in an environment.
• Clear writing. A large part of this job is skills, docs, and instructions that both humans and models follow.
• An interest in other developers’ pain points, especially people who are new to a platform, and the ability to design solutions that address those pain points.

What’s Nice To You Have

• Experience with “platform as a product” or developer experience work: interviewing users, caring about onboarding, measuring adoption.
• Experience maintaining AI skill files, agent instructions, MCP servers, or similar structured context for coding agents.
• Experience with Kubernetes-related developer tooling (Make, Kustomize, Helm) and with simplifying local workflows.
• Experience integrating software with Google Cloud Platform, AWS, or Azure.
• Experience with observability: tracing, logging, and metrics — including for AI workflows.