• Design, develop, test, iterate, and deploy secure production systems across cloud-native and edge appliance deployments • Embed with cross-functional teams and advise on infrastructure, security, and deployment best practices that hold up in production • Own end-to-end infrastructure outcomes for one or more critical programs or priority infrastructure initiatives • Harden the artifact pipeline so the same signed builds run in cloud, single-tenant high-side, and air-gapped appliance deployments

• Own and operate GPU and accelerator clusters • Design infrastructure that enables Kraken teams to run models locally • Build and improve scheduling, orchestration, placement, quota management • Optimize inference pipelines for latency, throughput, reliability • Partner with ML engineers to remove bottlenecks in workflows • Build observability for GPU utilization and capacity pressure • Drive reliability, incident response, and post-incident improvements • Evaluate and integrate new hardware and cloud resources • Contribute to long-term architecture decisions

• Own and operate GPU and accelerator clusters • Design infrastructure for local model execution • Build and improve scheduling and orchestration systems • Optimize inference pipelines • Partner with ML engineers to remove bottlenecks

• Own the FHIR R4 data model design • Architect and implement the HealthLake data layer including ingest pipelines • Lead the Supabase-to-HealthLake migration • Design and enforce encryption patterns and PHI access controls • Review and approve KMS infrastructure code • Build the data access layer consumed by agents • Implement audit logging infrastructure that satisfies HIPAA requirements • Design Clean Rooms configurations for analytics use cases