Software Engineer II

Couchbase, the operational data platform for AI, empowers businesses to succeed by bringing data to life in new ways. Major market-leading companies rely on Couchbase for mission critical operational, analytical, mobile and AI workloads. Built to replace legacy infrastructure and fragmented data services, Couchbase empowers enterprises with a unified platform architected for performance, flexibility and global scale.

With Couchbase, organizations bring their data to life, launching game‑changing customer experiences, exploring the limitless potential of AI, and seamlessly extending applications from the cloud to the edge and beyond. Couchbase’s AI‑ready technology and enterprise partnership model eliminate complexity and reduce total cost of ownership, enabling teams to stay agile, innovative and secure.

Couchbase believes data should never slow you down, but act as the foundation for your next breakthrough. Discover why Couchbase is trusted to help the world’s biggest players scale, move fast and stay resilient, no matter what’s next on their roadmap. Visit couchbase.com and follow us on LinkedIn and X.

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Couchbase Capella is a fully managed Cloud Database platform that powers mission-critical applications with a modern, distributed NoSQL database. The Control Plane Platform team builds and operates the foundational systems that deliver reliability, scalability, and seamless experiences across cloud environments, including Capella AI services and the advanced capabilities of the platform .

We are seeking a Software Engineer II to contribute to the design and development of Capella’s platform that orchestrates SaaS interactions with major cloud providers (AWS, GCP, Azure). In this role, you will implement features, debug code, and contribute to the overall quality and deployment readiness of the platform. You will also work on Capella Billing technologies, including reconciliation, scheduled jobs, and vendor integrations, and contribute to the integration and development of Capella AI services.

Key Responsibilities

• Engineer Feature Implementation: Implement features and bug fixes, ensuring adherence to design specifications, coding standards, and deployment readiness, including those related to Capella AI services.
• Code Testing and Debugging: Write unit tests for code, troubleshoot issues during the development process, and support debugging efforts during testing and post-deployment.
• Code Reviews: Participate in peer code reviews, providing and applying feedback to ensure quality and deployment readiness.
• Technical Documentation: Document code and features, ensuring clarity for future maintenance and deployment handoffs.
• SDLC Process Adherence: Follow SDLC procedures, including version control, branching strategies, and CI/CD practices.
• Support and Troubleshooting (Tier 2): Address escalated issues, performing root cause analysis and implementing solutions to improve reliability.
• Learning and Development: Continuously develop technical skills and contribute to team improvements in deployment and monitoring practices.
• Billing Technologies: Contribute to the development and maintenance of Capella Billing technologies, including reconciliation processes, scheduled jobs, and vendor integrations.
• AI Services Integration: Contribute to the development and integration of Capella AI services, ensuring seamless functionality within the platform.

Required Skills & Experience

• Experience in Golang with proven experience building distributed, cloud-native systems.
• Knowledge of system design, high availability, fault tolerance, and performance tuning.
• Hands-on experience with cloud infrastructure (AWS, GCP, Azure), including networking (VPCs, routing, load balancing, firewalls, private connectivity).
• Experience with Kubernetes, container orchestration, and multi-cloud deployments.
• Experience designing and building platform and microservice components for control planes of SaaS platforms.
• Hands-on problem solver who can balance strategic architecture with execution.
• Familiarity with billing systems and related technical concepts such as reconciliation, scheduled jobs, and vendor integrations.
• Understanding of AI/ML concepts and experience with integrating AI services into cloud platforms is a plus.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a…