[Hiring] Senior Platform Engineer @Anyone AI

Role Description

The role involves the development of the platform that runs Anyone AI’s Human Data work end to end. This includes:

• Standing up and evolving environments for RL, coding, STEM, and related evaluations.
• Leading pipeline and project-taxonomy design.
• Building the admin systems that keep production moving, including payments, task approval and rejection, roles, and visibility into project revenue and cost.

This is a high-autonomy seat: you lead the platform initiative. You need enough fluency in human data/evaluation workflows to make the right product and engineering calls without constant hand-holding.

Responsibilities

• Design, stand up, and harden RL, coding, STEM, and other evaluation environments that contributors and internal teams can reliably and repeatably run against at the quality bar labs expect.
• Lead platform development for how projects are structured: pipelines from brief → tasks → QC → delivery, plus project taxonomies that remain coherent as we add domains and clients.
• Support the operational layer: payments/payouts, task approve/reject flows, RBAC and roles management, and practical revenue & cost visibility per project.
• Set technical direction for the platform, prioritize ruthlessly between environment work, pipeline, and admin firefighting, and leave the system more instrumented and operable than you found it.

Experience

• Owned a multi-sided platform (operators + contributors + internal stakeholders), not only feature slices.
• Built or deeply operated systems in human data, RLHF, labeling, or model evaluation — or very close: RL/eval harnesses, annotation pipelines, coding/STEM eval environments.
• Shipped admin or back-office workflows: approvals, roles/permissions, payments or payouts, and operational metrics.
• Led a technical initiative with high ambiguity on a small team.

Qualifications

• Senior software engineer (4+ years, or equivalent ownership): backend or full-stack, comfortable owning a production web product and the services behind it.
• Proven autonomy; you can take a messy domain (human data/evals) and turn it into a roadmap and shipped systems.
• Working fluency with how frontier human-data and evaluation work actually runs (tasks, QC, environments, expert workflows) enough to design for it, not only implement specs.
• Nice to have: environment orchestration (containers, workers, sandboxes), prior work at or adjacent to Scale AI / Surge / Handshake AI / Labelbox / Other platforms, modern web/data stack familiarity.
• Fluent English. Spanish is a nice-to-have.