/roles — ROLE_161
Staff / Principal Platform Engineer
Well-funded AI lab shipping real-time voice and speech models used by major consumer apps
The role
- COMP
- $280K - $350K
- EQUITY
- Competitive equity
- LOCATION
- South Bay Area · San Francisco
- WORKPLACE
- Hybrid
- EXPERIENCE
- 8+ years
- VISA
- None, Visa transfers
- STACK
- Kubernetes, K8s, Terraform, Ansible, GCP, Azure, AWS, Go, Python, CI/CD, Docker, Git
- INDUSTRY
- AI, Software Development, API SDK
The company
AI research lab building highly ranked real-time voice models and developer APIs that power large consumer AI apps in areas like health, learning, companionship, and customer service.
- STAGE
- scale-up
- FUNDING
- $120M+ raised
- TEAM
- ~50 people
- FOUNDED
- 2021
- BACKING
- backed by Kleiner Perkins, Sequoia, Accel
JD — the work
About the role
A senior platform role with end-to-end ownership of the cloud infrastructure behind the company's text-to-speech and model-routing products, which serve consumer AI apps reaching hundreds of millions of people. You would run Kubernetes and infrastructure as code across several cloud providers, own CI/CD, and give engineering teams the tooling to operate their own services. The role also includes finding ways to speed up engineering with AI-powered tooling. It is hybrid in the San Francisco Bay Area.
What you'll do
- Build and operate fast, dependable, and secure infrastructure in the cloud for speech-generation and LLM-routing services
- Own delivery pipelines and infra rollouts with tooling like GitHub Actions, ArgoCD, and Terraform
- Help teams across the company ship and grow services on GCP, Azure, and Oracle Cloud
- Operate and grow Kubernetes clusters, authoring Helm charts and Kustomize configs for app deployments
- Give teams the monitoring and processes to own their services in production, from uptime to latency
- Lead root cause analysis and automate fixes so incidents do not repeat
- Find and build AI-driven tools and workflows that make engineers faster
What they're looking for
- 8+ years of software engineering, operating at staff or principal level
- Deep, hands-on Kubernetes and infrastructure-as-code expertise
- End-to-end ownership of large-scale cloud infrastructure in past roles
- History of running dependable, fast systems for consumer AI products
Nice to have
- Experience running AI or ML infrastructure
- Background supporting real-time, low-latency production workloads