Infrastructure Engineer, Customer Delivery

About Distyl AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s.

We're hiring a hands-on Infrastructure Engineer to lead cloud architecture and delivery of Distyl's AI platform across Distyl-hosted, customer VPC, and on-premises environments. You'll partner with customers, platform engineering, and forward-deployed AI engineers from discovery through production. Scope will reflect your experience, from leading complex deployments to setting technical direction across teams. You'll translate complex customer architectures and requests into working infrastructure, building reusable patterns and automation that make each launch easier. You'll own customer deployments end to end and help shape a growing delivery team's practices. Success means faster launches, reliable operations, and less repeated work as deployments scale.

Architecture ownership. Own portable reference architectures across Distyl-hosted, customer VPC, and on-premises deployments, with clear control-plane/data-plane boundaries. Distinguish necessary customer adaptations from avoidable variation across AWS, Azure, and GCP. Integrate identity, networks, data, and model providers with appropriate access, routing, and audit controls Platform and on-premises delivery. Work with forward-deployed AI engineers to deploy and upgrade Distyl's platform using infrastructure as code, Docker, Kubernetes, and shared CI/CD tooling. Support private registries, restricted egress, offline installs/upgrades, and alternatives to cloud-managed dependencies. Validate compatibility and recovery within customer change controls Automation mindset. Turn recurring delivery friction into shared automation. Build provisioning services, controllers, and reusable deployment APIs in Python or Go to make future deployments faster and more reliable Customer relationships and communication. Build trust, clarify requests, explain tradeoffs, and own commitments through production acceptance. Keep customers and developers aligned on readiness, upcoming changes, dependencies, and blockers; escalate risks early Production security and reliability. Implement network segmentation, data-residency controls, and audit trails with security and infrastructure partners. Establish SLOs, observability, actionable alerts, and tested disaster recovery. Own infrastructure incident resolution in assigned environments, coordinating with relevant engineering owners. Use incident and deployment data to improve reliability, runbooks, and support handoffs Hosted infrastructure. Build and operate tenant isolation, provisioning, quotas, autoscaling, metering, and cost attribution for Distyl-hosted deployments, in partnership with platform engineering AI runtime infrastructure. Partner with Runtime on agent sandboxing, workload identity, scoped credentials, network controls, and resource limits across supported deployments AI-assisted engineering. Build agent-assisted workflows for environment checks, troubleshooting, and infrastructure changes. Scope access, verify outputs, and