Software Engineer - Developer Experience
London Area, United Kingdom · Full Time
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Job description
About Neo4j
Neo4j provides an advanced graph intelligence platform that transforms complex data into actionable knowledge, fueling intelligent applications and AI systems. Trusted by 84 of the Fortune 100, Neo4j enables enterprise knowledge graphs with accuracy, explainability, and governance. Designed for seamless deployment across any environment and cloud, the platform drives rapid outcomes and contextual insights impacting organizations broadly.
Our Vision
We aim to empower organizations in a connected world by helping them understand and harness relationships in their data. As leaders in graph databases, we revolutionize the way data drives innovation and competitiveness.
The Team
Neo4j's Aura managed cloud service makes graph databases accessible in the cloud. We're launching the Aura DevEx team to enhance developer experience, improve onboarding, and simplify usage of the Aura platform. This team bridges database software development and the cloud environment, supporting users through person-to-person assistance, documentation, command-line tools, and AI integration. The team also manages AI-related development workflows, including agent skill files and instructions, ensuring safe collaboration between humans and AI agents.
The Role
As a Software Engineer in Developer Experience, your mission is to make Aura an accessible and efficient environment for all Neo4j teams. You will work closely with both new and seasoned users to reduce barriers in developing within Aura, improve tooling and documentation, and gather feedback to enhance developer workflows. Collaborating with Software Delivery and platform teams, you'll ensure a smooth, extensible developer platform without owning the delivery infrastructure.
Key Responsibilities
- Assist Neo4j Database engineers in integrating and developing within Aura by lowering platform-specific hurdles.
- Enhance developer workflows, documentation, and tools to support engineers focused on database components, services, or integrations.
- Support team onboarding and productivity without taking ownership of their products.
- Collaborate with the Software Delivery team to maintain reliable paths for developers.
- Provide feedback to platform teams to make the platform intuitive, user-friendly, and extensible.
- Maintain and update AI skill files and agent instructions to enable AI coding agents' compliance within Aura.
- Evaluate AI workflows considering quality, cost-efficiency, error modes, and productivity gains.
- Assist teams in adopting AI tools consistently without developing redundant stacks.
- Treat Developer Experience as a product by working closely with engineers to identify pain points and iterating based on usage data and feedback.
Required Qualifications
- Excellent collaboration and communication capabilities.
- Proficient with Golang, with experience spanning scripting to microservice applications.
- Familiarity with Golang's build and packaging systems.
- Strong software engineering background, having delivered tools such as CLIs, libraries, internal platforms, or developer-facing services.
- Basic understanding of Kubernetes concepts (Pods, Deployments, Docker images) sufficient to assist developers in Aura.
- Experience with modern CI/CD pipelines and Git workflows, managing code changes through to deployment.
- Clear and effective writing skills for creating documentation and instructional materials for both humans and AI models.
- Empathy for developer challenges, especially newcomers, with aptitude to design practical solutions.
Preferred Skills
- Background in platform-as-product or developer experience roles, including user research and adoption metrics.
- Experience managing AI skill files, coding agent instructions, or similar structured contexts.
- Experience with Kubernetes development tools such as Make, Kustomize, and Helm, plus local workflow simplification.
- Integration experience with cloud providers like Google Cloud Platform, AWS, or Azure.
- Familiarity with observability tools (tracing, logging, metrics), particularly for AI workflows.