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.

What We Are Looking For

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.

Key Responsibilities

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 measure improvements in delivery effort and reliability

Technical leadership. 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

Who You Are

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. You build trust, clarify requirements, negotiate scope, and keep stakeholders aligned

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, such as provisioning services, controllers, or deployment APIs

Experience operating hosted infrastructure with tenant isolation, provisioning, capacity controls, and usage/cost visibility

Experience turning customer requirements into production architectures, with clear control-plane/data-plane boundaries, 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. You balance speed with reliability, handle upgrades and stateful changes carefully, and verify AI-assisted work

Technical leadership. You lead complex deployments independently. Experience setting technical direction and leading adoption of reusable systems and standards across teams is especially valued

Strongly preferred: Building or scaling 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, including model access, routing, data-handling, and audit controls

What We Offer

The base salary range for this role is $200,000-$250,000, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package

100% coverage of medical, dental, and vision insurance for employee and dependents

Flexible time off

Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources

Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot

Complimentary in-office lunches and snacks provided

Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems

Ownership of high-impact projects across top enterprises

A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office.

#LI-Hybrid

We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.