A frontier data provider building the infrastructure layer that powers the next generation of foundational AI models.
Senior Platform Engineer, Applied AI
You'll own the platform that delivers high-fidelity training and evaluation data to the world's most advanced AI labs—scaling systems that move terabytes with precision under unpredictable workloads. This is a deeply technical, high-autonomy role where you'll harden multi-cloud infrastructure, tame distributed data pipelines, and instrument observability into every layer so research teams can move faster without breaking things. We're looking for someone who thinks in SLOs, builds for six-month horizons and six-minute incidents simultaneously, and believes that platform engineering is a product discipline.
What they're looking for
- 6–10 years building and operating distributed systems at scale, with deep fluency in Kubernetes, Kafka, and either AWS or GCP
- Strong programming in Python and NodeJS; comfortable profiling, debugging, and optimizing services across process and network boundaries
- Experience running data-intensive workloads involving Redis, ElasticSearch, and high-throughput streaming pipelines
- Track record of designing internal platforms with a product mindset—clear APIs, thoughtful defaults, and a sharp eye for developer experience
- On-site in San Francisco; able to shape early-stage infrastructure decisions while mentoring a small, senior team