• Design and maintain the pipelines that produce our Single-Tenant SaaS updates and our Self-Managed customer bundles. • Ensure "Build Once, Deploy Anywhere" consistency across standard cloud and restricted GovCloud environments. • Manage artifact lifecycle, including versioning, container registries, and software signing to meet federal security standards. • Act as the primary technical point of contact for ISSM (Information System Security Manager) approvals for GovCloud deployments. • Maintain the "Version Map"—tracking which customers are on which versions and managing the complexities of "version lag" for those who opt out of weekly updates. • Coordinate across teams to validate bundles before they are shipped to customer-managed environments. • Continually improve our release operations and processes through automation • Develop and track metrics for release operations, recommend and develop solutions to improve alongside the engineering team. • Lead "Go/No-Go" decisions, synthesizing input from QA, Support, and Product. • Empower Customer Support and Sales Engineering by providing them with clear "Known Issues" lists and migration paths for each release, with the support of the engineering and product team for input.

• Architect and operate high-availability, low-latency cloud infrastructure for real-time AI inference services. • Build and maintain CI/CD pipelines that support rapid, safe iteration across backend and ML systems. • Own production reliability: monitoring, alerting, incident response, and capacity planning. • Lead infrastructure automation using Infrastructure as Code (Terraform, Pulumi, etc.). • Partner closely with backend and ML engineers to productionize new models and services. • Harden our systems for security, compliance, and data protection. • Optimize cost, performance, and scalability as usage grows. • Establish best practices around observability, deployment strategies, and disaster recovery.

• Improve deployment reliability, reduce operational risk, and help modernize AWS infrastructure toward Kubernetes. • Support the whole Engineering organization, building applications on top of EC2 and AWS. • Own all aspects of the SDLC and strive to automate self-service wherever possible. • Continuously improve observability and build with Infrastructure-as-Code. • Ensure systems are secure by design and meet regulatory and organizational standards.

• Improve deployment reliability and reduce operational risk • Help modernize AWS infrastructure toward Kubernetes • Support whole Engineering organization building applications on top of EC2 and AWS • Own all aspects of the SDLC while striving to automate self-service wherever possible • Practice SRE, continuously improving observability and building with Infrastructure-as-Code