Remote Staff Software Engineer — AI Platform & Infra Lead

Cake; United States; Remote; USD 210,000 - 320,000; Full time

Benefits offered by this job

High ownership

Senior team

Competitive compensation

Medical insurance

401k

Unlimited PTO

Wellness stipend

Learning & growth opportunities

Job summary

Cake is seeking a Staff Software Engineer to lead infrastructure powering its AI platform. This high‑ownership role focuses on distributed systems, cloud infrastructure, and developer experience, with production ownership from architecture to deployment.

You will design and operate platform foundations, partner with customers to translate ML needs into reliable capabilities, and mentor engineers across the organization.

Qualifications

• 10+ years in engineering with infrastructure or distributed systems.
• Hands-on Kubernetes production experience.
• Cloud experience: AWS, GCP, or Azure.
• Proven experience building secure, scalable AI/ML platforms.
• Experience with infrastructure-as-code (Terraform, Pulumi, CDK).
• Strong backend programming in Go (preferred) or TypeScript.
• Experience diagnosing production issues and with CI/CD/DevSecOps.
• Ownership mindset and excellent communication.

Responsibilities

• Build Enterprise-Scale Infrastructure
• Design Kubernetes-native systems
• Improve platform networking, security, and observability
• Own critical systems in production
• Create abstractions and tooling to deploy, run, and scale AI/ML workloads
• Collaborate directly with customers to translate ML needs into platform improvements
• Lead through influence; write docs and proposals and partner with leadership to shape direction

Skills

Kubernetes

Go

TypeScript

AWS/GCP/Azure

Distributed systems

CI/CD/DevSecOps

Customer communication

Tools

Terraform

Pulumi

CDK

Istio

Crossplane

Job description

Cake is seeking a Staff Software Engineer to lead infrastructure powering its AI platform. This high‑ownership role focuses on distributed systems, cloud infrastructure, and developer experience, with production ownership from architecture to deployment.

You will design and operate platform foundations, partner with customers to translate ML needs into reliable capabilities, and mentor engineers across the organization.