• 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.

• Design and evolve the systems, tooling, and processes that improve the reliability and performance of WorkOS • Collaborate with product and infrastructure teams to ensure services are production-ready, observable, and resilient to failure • Define and measure SLIs/SLOs to guide reliability improvements • Write and optimize backend systems (in TypeScript) with a focus on performance, maintainability, and graceful degradation • Improve our incident response process, lead postmortems, and drive follow-through on reliability risks • Develop internal tools and automations that make it easier to operate and scale our systems • Participate in our on-call rotation—responding to, resolving, and learning from production incidents • Contribute to design and architecture discussions with a focus on operability and long-term sustainability • Document systems, share learnings, and help grow a reliability-minded engineering culture

• Automate deployment and operations of large-scale RDMA (RoCEv2) Ethernet fabrics across Vultr data centers. • Build Ansible and Python-based frameworks to provision, validate, and remediate underlay and overlay networks. • Integrate network automation with Vultr’s source-of-truth systems (NetBox, OpsMill) for intent-driven configuration and validation. • Develop telemetry ingestion and correlation pipelines (gNMI, Prometheus, Kafka, custom collectors) for real-time network health and performance metrics. • Collaborate with platform, orchestration, and product engineering teams to optimize RDMA performance, PFC/ECN behavior, and path symmetry across fabrics. • Implement CI/CD workflows for network configuration changes — validation, pre-checks, and rollbacks. • Investigate complex network behaviors across layers — flow hashing, congestion domains, ECMP, and overlay interactions. • Contribute to the design of next-generation GPU and AI interconnect fabrics, ensuring seamless integration into Vultr’s global network architecture.