Infrastructure Engineer, Customer Delivery

Distyl AI

. Lead cloud architecture and delivery of Distyl's AI platform across Distyl-hosted, customer VPC, and on-premises environments .

Posted 10/14/2026full-timeUnited StatesSeniorLead💰 $200,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in cloud architecture and infrastructure engineering, with a strong focus on AWS, Azure, and GCP. Capable of translating customer requirements into production-ready solutions while ensuring compliance with security and operational standards.

Highest-signal resume keywords

Cloud ArchitectureInfrastructure As CodePython DevelopmentKubernetes ManagementCustomer-Facing Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Infrastructure EngineeringCloud EngineeringSite Reliability EngineeringNetworkingIAMDockerObservabilityProduction DeploymentsTenant IsolationAutomation

Soft Skills

Stakeholder CommunicationTroubleshootingMentoring

Tools & Technologies

AWSAzureGCPCI/CDPrivate RegistriesDisaster RecoveryAgent Sandboxing

Industry Keywords

Data-Residency ControlsNetwork SegmentationAudit TrailsSLOsIncident Response

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPythonGo

About the role

Key responsibilities & impact

Lead cloud architecture and delivery of Distyl's AI platform across Distyl-hosted, customer VPC, and on-premises environments
Partner with customers, platform engineering, and forward-deployed AI engineers from discovery through production
Translate customer architectures and requests into working infrastructure, reusable patterns, and automation
Own portable reference architectures across AWS, Azure, and GCP
Deploy and upgrade the 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
Build provisioning services, controllers, and reusable deployment APIs in Python or Go
Manage customer relationships, clarify requirements, explain tradeoffs, and maintain alignment through production acceptance
Implement network segmentation, data-residency controls, audit trails, SLOs, observability, alerts, and disaster recovery
Own infrastructure incident resolution and improve reliability, runbooks, and support handoffs
Build and operate tenant isolation, provisioning, quotas, autoscaling, metering, and cost attribution for hosted deployments
Partner on AI runtime infrastructure including agent sandboxing, workload identity, scoped credentials, network controls, and resource limits
Build agent-assisted workflows for environment checks, troubleshooting, and infrastructure changes
Set delivery standards, mentor engineers, and turn customer lessons into product improvements

Requirements

What you’ll need

7+ years of experience in infrastructure engineering, cloud engineering, SRE, 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
Hands-on experience with networking, IAM, 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
Experience operating hosted infrastructure with tenant isolation, provisioning, capacity controls, and usage/cost visibility
Experience turning customer requirements into production architectures with CI/CD 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, SLOs, disaster recovery, and incident response
Strong troubleshooting and automation skills
Experience leading complex deployments independently and setting technical direction across teams
Strongly preferred: infrastructure delivery and operations across enterprise customer environments, including production deployments across multiple clouds
Preferred: on-premises installs/upgrades, offline operation, or replacing cloud-managed dependencies
Preferred: agent sandboxing or technical AI governance

Benefits

Comp & perks

Meaningful equity
100% coverage of medical, dental, and vision insurance for employee and dependents
Flexible time off
Pre-tax HSA, FSA, and commuter accounts
401(k)
Financial coaching resources
Physical fitness, mental well-being, and fertility and family-building benefits through Carrot
Complimentary in-office lunches and snacks
Access to state-of-the-art AI models and generous usage of modern AI tools
Ownership of high-impact projects across top enterprises