Platform Engineer

Nxt Level; San Francisco (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

Nxt Level in San Francisco is hiring a Platform Engineer, Data Production to build and scale the internal platform powering data production across the company. You will focus on making the platform more feature-rich, reliable, scalable, and tightly integrated with the research and data teams to accelerate high-quality outputs.

The ideal candidate is a strong systems engineer who can reason deeply about distributed systems, platform architecture, and dev workflows, thriving in an intense

Qualifications

• Experience with distributed systems and infrastructure.
• Ability to reason through low-level infrastructure problems and async I/O.
• Fast problem-solving in systems-heavy environments.
• Strong collaboration with research, data, and engineering teams.

Responsibilities

• Build and scale the internal data-production platform.
• Create systems to meet frontier AI lab demand.
• Improve reliability, performance, and scalability.
• Integrate platform with research and data teams.
• Design infrastructure to enable faster, higher-quality outputs.
• Own core systems across data production workflows.
• Debug platform issues and improve long-term health.
• Develop tools and abstractions for repeatable data production.
• Collaborate with founders and engineers to ship improvements.
• Help define platform architecture and standards.

Skills

Distributed systems

Platform engineering

System debugging

Ownership

Job description

Profile:

Systems/platform engineer with strong infrastructure depth and high ownership

About Our Client

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.

About the Role

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.

What You’ll Do

• 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

What We’re Looking For

• 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

Bonus Experience

• 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

Who Will Thrive Here

• A systems/platform engineer who wants to own the backbone of a frontier‑lab data product
• A fast problem‑solver who enjoys debugging and building infrastructure
• Someone who is highly committed, results‑driven, and energized by intense early‑stage work
• An engineer who wants to work close to researchers and data teams without being in a research role
• A builder who cares about reliability, scale, and making internal users dramatically more effective
• Someone comfortable in person with an ambitious team that is moving quickly by choice

Why This Opportunity

• Own the internal platform that powers a frontier AI data product
• Build critical infrastructure for a company serving advanced AI lab demand
• Work directly with founders and technical teams with deep systems backgrounds
• Solve hard platform problems across scale, reliability, integration, and workflow design
• Help make research and data teams more productive through better systems
• Join early enough to shape platform architecture, engineering standards, and technical culture
• Step into a role where infrastructure work directly impacts customer capacity and company growth

Ideal Candidate Profile

The ideal candidate is a systems‑minded platform engineer who wants to build the infrastructure backbone of a high‑demand AI data company.

They are strong in distributed systems, infrastructure, debugging, and scaling. They move fast, understand code quickly, and care about building platforms that let research and data teams produce better work at higher throughput.

This person is not looking for a pure research role. They want to build the systems that make the research and data engine scale.