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Greenlite AI

Software Engineer, Infrastructure

full-time•San Francisco•$168k - $213k

Summary

Location

San Francisco

Salary

$168k - $213k

Type

full-time

Experience

5-10 years

Company links

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About this role

About the role

As a Senior Infrastructure Engineer at Greenlite, you'll own the foundation that lets us deploy secure, compliant AI systems at major financial institutions fighting financial crime at massive scale. Our infrastructure is built on a modern container-native architecture, leveraging Docker and Kubernetes orchestrated through platform automation tools like ryvn.ai to deliver consistent, auditable deployments across diverse customer environments.

You'll work directly with our biggest customers—institutions serving over a billion people—architecting, automating, and hardening our on-premises and cloud environments to meet the strictest regulatory and performance requirements, including SOC 2 compliance. Your infrastructure work is informed by real customer needs and ships to everyone, so you need to build enterprise-grade systems, work effectively with engineering and customer teams, understand financial services compliance, and adapt quickly.

This is a core infrastructure role on our Engineering team. You're an exceptional infrastructure engineer who understands that financial institutions need hyperscale reliability when deploying AI for compliance workflows. You'll lead reliability and scalability initiatives, architect secure infrastructure, and mentor others as we scale. You're not just building infrastructure—you're engineering enterprise-grade systems based on what our most sophisticated customers actually need for regulatory compliance and performance.

Please Note: We work in-person Monday through Friday in our SF office.

What you'll do

Month 1:

  • Master our Kubernetes-based AI infrastructure platform and container orchestration workflows

  • Get hands-on with our ryvn.ai platform automation tooling, Datadog observability stack, and deployment pipelines

  • Shadow experienced engineers on customer on-premises and private cloud rollouts

  • Lead your first incident response and begin modeling system growth patterns

Month 2:

  • Own end-to-end infrastructure architecture for major bank and fintech deployments

  • Build and implement enterprise-grade CI/CD frameworks with embedded security, SOC 2 compliance gates, and progressive delivery mechanisms

  • Partner with customer engineering teams on complex cloud and on-premises deployments

  • Become the go-to expert for regulated AI infrastructure at scale

Ongoing:

  • Own and evolve our Kubernetes infrastructure, including cluster management, service mesh configuration, and container security policies

  • Design and implement progressive delivery pipelines with canary deployments, automated rollbacks, and deployment health validation

  • Build and maintain observability infrastructure in Datadog, including dashboards, monitors, SLOs, and distributed tracing

  • Drive incident response for high-severity outages and proactively model capacity needs for low-latency AI inference

  • Architect and automate secure infrastructure using Infrastructure-as-Code for VPCs, IAM policies, Kubernetes manifests, and private cloud deployments

  • Maintain and improve infrastructure controls supporting our SOC 2 compliance posture

  • Lead customer engagements for enterprise rollouts and mentor mid-level engineers on infrastructure best practices

What we're looking for

  • 8+ years in infrastructure engineering or DevOps at high-growth or hyperscale companies

  • Experience with Docker and Kubernetes, including production cluster management, Helm, and service mesh technologies

  • Proven track record of architecting and operating AWS (preferred), GCP, or Azure at enterprise scale

  • Experience with observability platforms, preferably Datadog (metrics, logs, APM, distributed tracing)

  • Strong background in Infrastructure-as-Code (Terraform, Helm, Kustomize) and safe deployment practices (progressive delivery, canary deployments, GitOps, automated rollbacks)

  • "Battle scars" from leading outages, capacity events, and large-scale incident reviews

  • Strong programming skills in Python; familiarity with TypeScript a plus

  • Experience mentoring engineers and leading technical initiatives

Bonus points:

  • Experience with platform engineering tools like ryvn.ai, or similar

  • Direct involvement in SOC 2 or other compliance audit preparation or remediation

  • Direct experience with private-cloud or on-premises deployments for regulated customers

  • Previous experience at startups scaling infrastructure from early stage to enterprise

  • Background in fintech or building systems for highly regulated industries

  • Experience with AI/ML infrastructure and model deployment at scale

About you

You're a senior infrastructure engineer who thrives at the intersection of technical leadership and customer impact. You see infrastructure as a product for your engineering peers and understand the value of platform automation in enabling developer velocity while maintaining security and compliance guardrails.

You understand that effective infrastructure engineering means building systems that enable rapid development while maintaining the highest standards of security, compliance, and reliability. You're comfortable balancing technical excellence with mentoring others and leading customer engagements, and you want your infrastructure contributions to have direct, measurable impact on how financial institutions adopt AI to fight crime.

Compensation & Benefits

  • $168k - $213k + equity

  • Comprehensive healthcare, 401k matching, commuter benefits

  • 15 days PTO + holidays, unlimited sick days

  • Flexible leave options

  • Working late? We've got you covered with DoorDash and an Uber home

Join us in building AI that protects the global financial system from financial crimes that fund terrorism, human trafficking, and other serious threats.

What you'll do

  • The role involves owning and evolving the Kubernetes infrastructure, designing progressive delivery pipelines, and building/maintaining observability infrastructure using tools like Datadog. Responsibilities also include architecting and automating secure infrastructure using Infrastructure-as-Code and driving incident response for high-severity outages.

About Greenlite AI

Greenlite builds AI agents for compliance teams. Agents handle routine work inside of your existing AML tools, like clearing alerts, remediating backlogs or conducting periodic reviews. Trusted by compliance teams at Ramp, Coastal Community Bank, Grasshopper Bank, First Internet Bank, Betterment and more.

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Frequently Asked Questions

What does Greenlite AI pay for a Software Engineer, Infrastructure?

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Greenlite AI offers a competitive compensation package for the Software Engineer, Infrastructure role. The salary range is USD 168k - 213k per year. Apply through Clera to learn more about the full compensation details.

What does a Software Engineer, Infrastructure do at Greenlite AI?

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As a Software Engineer, Infrastructure at Greenlite AI, you will: the role involves owning and evolving the Kubernetes infrastructure, designing progressive delivery pipelines, and building/maintaining observability infrastructure using tools like Datadog. Responsibilities also include architecting and automating secure infrastructure using Infrastructure-as-Code and driving incident response for high-severity outages..

Is the Software Engineer, Infrastructure position at Greenlite AI remote?

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The Software Engineer, Infrastructure position at Greenlite AI is based in San Francisco, United States. Contact the company through Clera for specific work arrangement details.

How do I apply for the Software Engineer, Infrastructure position at Greenlite AI?

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You can apply for the Software Engineer, Infrastructure position at Greenlite AIdirectly through Clera. Click the "Apply Now" button above to start your application. Clera's AI-powered platform will help match your profile with this opportunity and guide you through the application process.
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