Platform Engineer, Data Production

NxT Level•San Francisco, CA

6d•Onsite

About The Position

Our client is building data infrastructure for frontier AI labs. As demand from advanced AI customers continues to grow, the company is scaling the internal platform that produces its core data product. While some roles on the team blend research and data production, this role is focused more directly on the systems, infrastructure, and platform backbone that makes high-quality data production possible at scale. This is an opportunity to own critical platform infrastructure inside an intense, early-stage technical team building for frontier-lab demand. Our client is hiring a Platform Engineer, Data Production to build and scale the internal platform that powers data production across the company. This person will focus on making the platform more feature-rich, reliable, scalable, and tightly integrated with the research and data teams. The work is core systems and infrastructure engineering — building the foundation that allows research and data teams to produce high-quality outputs faster and more repeatably. The ideal candidate is a strong systems engineer who can reason deeply about distributed systems, platform architecture, reliability, scale, and developer workflows.

Requirements

Strong software engineering and infrastructure engineering background
Experience with distributed systems, platform engineering, scaling, or systems infrastructure
Strong code comprehension and ability to debug unfamiliar systems quickly
Fast problem-solving ability in practical, systems-heavy environments
Ability to reason through low-level infrastructure problems, async I/O, runtime behavior, distributed systems issues, or similar technical challenges
High ownership, urgency, and bias toward results
Comfort operating in an intense, early-stage startup environment
Ability to build reliable systems without unnecessary process or overhead
Strong collaboration with research, data, and engineering teams
High-slope learning profile and deep commitment to the work

Nice To Haves

Experience building internal platforms for research, data, ML, or AI teams
Experience with distributed databases, network infrastructure, or large-scale backend systems
Experience building tooling for data production, evaluation, annotation, or model workflows
Experience working in high-performance technical teams or frontier AI-adjacent environments
Experience debugging production systems, runtimes, async systems, or infrastructure bottlenecks
Experience scaling internal platforms from early usage to high-demand production workflows

Responsibilities

Build and scale the internal data-production platform
Create systems that help the company meet growing demand from frontier AI labs
Improve reliability, performance, and scalability across the platform
Build tight integrations between platform systems and the research/data organization
Design infrastructure that helps researchers and data teams produce work faster and with higher quality
Own core systems and infrastructure work across data production workflows
Debug complex platform issues and improve long-term system health
Build tools, services, and abstractions that make data production more efficient and repeatable
Partner closely with founders, researchers, data teams, and engineers to identify bottlenecks and ship improvements
Help define platform architecture and engineering standards as the company scales