• Design, build, and run reliable, scalable infrastructure with a strong platform engineering and SRE mindset. • Lead platform engineering initiatives using Kubernetes (EKS), Helm, and Infrastructure as Code. • Design and operate CI/CD platforms and deployment strategies to enable safe, low-risk releases. • Build and maintain strong observability foundations, including metrics, logging, alerting, and dashboards tied to service health. • Design, build, and operate scalable, secure AWS infrastructure, including VPCs, subnets, routing, NAT, VPNs, and Transit Gateway. • Own and evolve cloud networking and connectivity architecture, ensuring secure, reliable, and performant communication between services. • Configure and manage Cloudflare to support edge security (including WAF, DDoS protection, and rate limiting), optimize CDN performance and caching strategies, and handle DNS and traffic management. • Actively participate in incident response, root cause analysis, and blameless post-mortems to drive durable corrective actions. • Strengthen security and compliance across infrastructure, including IAM, network security, container security, and SOC2 alignment. • Define and improve service reliability through SLIs, SLOs, and error budgets. • Reduce operational toil through automation and standardized platform patterns. • Identify and drive cost optimization, including cloud and network egress efficiency. • Mentor engineers and contribute to a collaborative, high-performance engineering culture.

• Lead the initial setup of our DevOps and platform engineering practices, defining standards, tooling, and infrastructure strategy • Design and deliver an internal platform for personal or feature environments to empower developers and improve velocity • Build and maintain AWS-based infrastructure to ensure optimal performance, scalability, and security • Develop CI/CD pipelines to streamline deployments and automate release processes • Implement observability tooling (logging, monitoring, alerting) to detect and resolve issues proactively • Collaborate closely with developers to identify bottlenecks, improve delivery, and enhance system reliability • Ensure high availability and uptime through effective monitoring, incident response, and recovery strategies • Promote infrastructure automation and Infrastructure as Code best practices • Document systems, configurations, and incident processes for team-wide clarity and consistency • Participate in on-call rotations or coordinate time zone coverage to ensure 24-hour reliability across regions

• Design and manage infrastructure deployments using Docker, Kubernetes, and AWS/GCP. • Develop secure key management systems for API keys and wallet abstraction. • Implement monitoring, logging, and incident handling for execution nodes. • Set up CI/CD pipelines and streamlined developer workflows (GitHub Actions). • Optimize infrastructure for reliability, security, and scalability. • Collaborate with backend engineers to support execution and receipts systems.

• Own the reliability, performance, and scalability of WorkOS's PostgreSQL infrastructure. • Analyze and implement best practices for our database clusters, including replication, connection pooling, high availability, and disaster recovery. • Build and maintain observability for database metrics (query performance, replication lag, connection saturation, storage growth) and ensure we meet our database SLOs. • Provide database expertise to product engineering teams through migration reviews, query optimization guidance, and schema design consultation. • Develop automation and self-service tooling that enables engineers to safely interact with databases without bottlenecking on the DBRE team. • Participate in on-call rotations and lead incident response for database-related production issues, performing root cause analysis and implementing permanent fixes. • Plan and manage database capacity, forecasting growth and ensuring our infrastructure can handle increased workloads. • Collaborate with SREs to roll out infrastructure changes to production environments, with a focus on minimizing risk to the data layer. • Document operational procedures, runbooks, and architectural decisions so learnings become repeatable actions and eventually automation. • Drive improvements to backup and recovery strategies, regularly testing and validating disaster recovery procedures.