About the role
We're looking for an all-round infrastructure engineer who writes production-grade code, designs systems from first principles, and owns everything from infrastructure-as-code to a multi-cloud ML serving stack. You'll be joining a small, elite infrastructure team that owns it all.
What you will do
Lead infrastructure architecture across the company and take end-to-end ownership across Onyx's infrastructure - cloud environments, platform tooling, internal services, and production uptime
Design and build production-grade services and internal platform tooling; you write code at the same bar as the product engineering team
Operate and scale AI/ML Serving Infrastructure systems behind real-time LLM routing, model inference, and AI security enforcement in production
Requirements
What you will bring
6+ years in infrastructure, platform, DevOps, or SRE roles - with strong software engineering ability, not just operational experience
Production-grade cloud expertise (AWS, GCP or Azure) - deep understanding of compute, networking, data services, identity, and security across cloud providers
Hands-on experience building and running AI/ML infrastructure in production - model serving, inference workloads
Kubernetes depth - you operate clusters in production, understand the internals, and debug the problems others escalate
Infrastructure-as-code at scale - you've designed module architectures, managed state across environments, and integrated it all into CI/CD
Experience building an internal developer platform - you've designed the tooling, pipelines, and abstractions that engineering teams depend on
Strong coding ability in Go, Python, or Node.js - you build and own services, not just glue scripts
Security-first thinking embedded in how you design and operate systems
What you will bring
6+ years in infrastructure, platform, DevOps, or SRE roles - with strong software engineering ability, not just operational experience
Production-grade cloud expertise (AWS, GCP or Azure) - deep understanding of compute, networking, data services, identity, and security across cloud providers
Hands-on experience building and running AI/ML infrastructure in production - model serving, inference workloads
Kubernetes depth - you operate clusters in production, understand the internals, and debug the problems others escalate
Infrastructure-as-code at scale - you've designed module architectures, managed state across environments, and integrated it all into CI/CD
Experience building an internal developer platform - you've designed the tooling, pipelines, and abstractions that engineering teams depend on
Strong coding ability in Go, Python, or Node.js - you build and own services, not just glue scripts
Security-first thinking embedded in how you design and operate systems
