Senior Platform Engineer, Human Data — Anyone AI

Anyone AI Labs posted a fully remote Senior Platform Engineer, Human Data role for its Human Data Division, which owns the company's RL, coding, and STEM evaluation environments, pipelines and project taxonomies, and admin/ops surface. The posting lists no salary, and the job board notes that 188 of its 428 Senior AI Agents roles publish pay, with a median of $195k and a middle half range of $169k–$221k. The position requires 4+ years of senior backend or full-stack engineering experience and fluency in human data, RLHF, labeling, or model evaluation workflows, with Spanish listed as a nice-to-have.

Senior Platform Engineer, Human Data At a glance - Salary - Not published - Location - Fully Remote - Work type - Remote - Level - Senior - Posted - today - Verified live - today - Skills - OrchestrationEval harnessesRLHF - Filed under - AI Agents https://frontierroles.com/ai-agent-jobs/ Evals & Quality https://frontierroles.com/ai-eval-jobs/ Fine-tuning https://frontierroles.com/fine-tuning-jobs/ How the pay compares This posting doesn't publish pay. 188 of the 428 Senior AI Agents roles https://frontierroles.com/ai-agent-jobs/ on this board do: the middle half pay $169k–$221k , with a median of $195k . Middle half of the 188 that publish payMedian10th–90th percentileAnnual, USD Apply on company site opens in new tab https://jobs.ashbyhq.com/anyone-ai/e95e8fdf-888e-4bac-b303-7fb0211c0fe2/application Job description Anyone AI Labs — Anyone AI’s Human Data Division Owns: the Human Data platform RL / coding / STEM evaluation environments, pipelines & project taxonomies, and the admin/ops surface like payments, task approve/reject, roles, revenue & cost Location: Remote / LatAm / US The role Development of the platform that runs Anyone AI’s Human Data work end to end. That means standing up and evolving environments for RL, coding, STEM, and related evals; leading pipeline and project-taxonomy design; and building the admin systems that keep production moving, 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 ● Evaluation environments. Design, stand up, and harden RL, coding, STEM, and other eval environments that contributors and internal teams can actually run against reliably, repeatably, and at the quality bar labs expect . ● Pipelines & taxonomies. Lead platform development for how projects are structured: pipelines from brief → tasks → QC → delivery, plus project taxonomies that stay coherent as we add domains and clients. ● Admin & operations surface. support the operational layer: payments / payouts, task approve/reject flows, RBAC and roles management, and practical revenue & cost visibility per project. ● Lead the initiative. Set technical direction for the platform, prioritize ruthlessly between env 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: env 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.