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Distyl AI

Builds AI systems for enterprise operations

Infrastructure Engineer - Customer Delivery

Platform Engineering +1Confirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Seven or more years of experience in infrastructure engineering, cloud engineering, site reliability engineering, or related technical delivery roles.
  • Deep production experience in AWS, Azure, or GCP, plus working experience in a second cloud.
  • Customer-facing engineering experience with direct responsibility for technical delivery and stakeholder communication, including clarifying requirements, negotiating scope, and keeping stakeholders aligned.
  • Hands-on experience with networking, identity and access management, Docker, Kubernetes, and observability, including workload identity, scoped credentials, and resource limits.
  • Proven experience writing and maintaining production infrastructure as code.
  • Strong production Python or Go experience building reusable infrastructure software, such as provisioning services, controllers, or deployment APIs.
  • Experience operating hosted infrastructure with tenant isolation, provisioning, capacity controls, and usage and cost visibility.
  • Experience turning customer requirements into production architectures with clear control-plane and data-plane boundaries, continuous integration and delivery, and identity, network, and data integrations.
  • Experience delivering under strict access, network, security, and change controls, including private registries or restricted egress.
  • Experience implementing network segmentation, data-residency controls, audit trails, service-level objectives, disaster recovery, and incident response.
  • Strong troubleshooting and automation skills, careful handling of upgrades and stateful changes, and ability to verify AI-assisted work.

Responsibilities

  • Own portable reference architectures across Distyl-hosted, customer VPC, and on-premises deployments, with clear control-plane and data-plane boundaries; distinguish necessary customer adaptations from avoidable variation across AWS, Azure, and GCP; and integrate identity, networks, data, and model providers with appropriate access, routing, and audit controls.
  • 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 and upgrades, and alternatives to cloud-managed dependencies; and validate compatibility and recovery within customer change controls.
  • Build provisioning services, controllers, and reusable deployment APIs in Python or Go to turn recurring delivery friction into shared automation and make future deployments faster and more reliable.
  • Build customer trust, clarify requests, explain tradeoffs, and own commitments through production acceptance; keep customers and developers aligned on readiness, upcoming changes, dependencies, and blockers; and escalate risks early.
  • 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 while coordinating with relevant engineering owners; and use incident and deployment data to improve reliability, runbooks, and support handoffs.
  • Build and operate tenant isolation, provisioning, quotas, autoscaling, metering, and cost attribution for Distyl-hosted deployments in partnership with platform engineering.
  • Partner with Runtime on agent sandboxing, workload identity, scoped credentials, network controls, and resource limits across supported deployments.
  • Build agent-assisted workflows for environment checks, troubleshooting, and infrastructure changes; scope access, verify outputs, and measure improvements in delivery effort and reliability.
  • Set delivery standards, mentor engineers, and help build the delivery team's technical practices; partner with forward-deployed AI and platform engineers to unblock delivery and turn customer lessons into product improvements.

Desired Qualifications

  • Experience setting technical direction and leading adoption of reusable systems and standards across teams.
  • Experience building or scaling infrastructure delivery and operations across enterprise customer environments, including production deployments across multiple clouds.
  • Experience with on-premises installs or upgrades, offline operation, or replacing cloud-managed dependencies.
  • Experience with agent sandboxing or technical AI governance, including model access, routing, data handling, and audit controls.

About the Company

Distyl AI

Builds AI systems for enterprise operations

Distyl AI builds AI systems for large enterprises that need to automate complex business operations rather than isolated tasks. Its Distillery platform brings the tools for creating and running those systems together, while engineers and researchers work alongside customers to define the problem and put solutions into use. The company combines purpose-built software with implementation engagements across telecom, healthcare, insurance, manufacturing and retail, covering work such as customer service and supply chain decisions. Customers buy tailored enterprise deployments that connect business expertise with AI tools and are measured against operational outcomes. Founded in 2022, Distyl AI is headquartered in San Francisco, California.

Company size
51-200
Company stage
Late Stage VC
Total funding
$202M
Headquarters
San Francisco, CA
Founded
2022

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