Principal Software Engineer

Principal Software Engineer – Capella Control Plane Platform

Location: San Jose, California

Couchbase Capella is a fully managed Database-as-a-Service (DBaaS) 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.

We are seeking a Principal Software Engineer to lead the architecture of Capella’s Control Plane — the platform that orchestrates SaaS interactions with major cloud providers (AWS, GCP, Azure). In this role, you will mentor engineers, deliver core platform capabilities, and combine hands-on development with deep expertise in distributed systems and cloud architecture leadership, while contributing to the architecture and integration of state-of-the-art AI/ML knowledge and process execution into the Capella Control Plane.

Key Responsibilities

• System Design & Architecture: Define and evolve the control plane architecture for scalability, reliability, performance, and security.
• Hands-on Development: Develop and deliver production-quality Golang code for critical Capella platform services. Participate in, and help guide the team on Golang coding standards and strategies.
• Cloud Infrastructure & Networking: Architect and optimize multi-cloud deployments, networking models, VPC/VNet peering, load balancing, and secure connectivity for Capella.
• Cloud-First SaaS Expertise: Build and scale multi-tenant control plane services that orchestrate Couchbase clusters across cloud providers.
• Technical Standards: Establish and enforce coding standards with strong code reviews, CI/CD practices, and design patterns.
• Observability & Reliability: Define and implement monitoring, logging, tracing, and alerting standards for operational excellence.
• High-impact Features: Lead design and delivery of core platform capabilities such as provisioning, lifecycle management, and security controls.
• Problem Solving: Tackle complex distributed systems challenges and resolve scaling, networking, and performance bottlenecks.
• Cross-functional Collaboration: Work with product, SRE, Quality Engineering, and operations teams to align technical direction with business goals.
• Multi-geo Team Collaboration: Partner effectively with global engineering teams across geographies, driving alignment and execution.
• Mentorship & Leadership: Guide junior and mid-level engineers, conduct reviews, and set a high bar for engineering culture. Perform code reviews in your area of influence.
• Innovation: Research and evaluate cloud-native technologies, frameworks, and architectures for Capella’s evolution. Lead the technical strategy, design, and integration of AI/ML services and foundational models into the control plane to enhance platform capabilities and execution efficiency.
• Support & Troubleshooting (Tier 3): Lead root cause analysis and deliver long-term solutions for critical production issues.
• Define and optimize processes for AI model deployment, lifecycle management, and observability within the multi-cloud architecture.

Required Skills & Experience

• Expertise in Golang with proven experience building distributed, cloud-native systems.
• Strong 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 plane of SaaS platforms.
• Experience mentoring engineers and influencing the engineering culture.
• Hands-on problem solver who can balance strategic architecture with execution.
• Demonstrated experience with AI/ML platform architecture and integrating advanced AI/ML services (e.g., vector databases, foundational models) into large-scale, production-ready SaaS platforms.
• Strong understanding of data pipelines and model serving infrastructure necessary for state-of-the-art AI process execution.

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

• 12 years of professional software engineering experience, with at least 5 years in cloud/distributed systems.

• Prior principal or staff engineer-level experience leading architecture and platform initiatives in DBaaS, cloud infrastructure, or large-scale SaaS environments.