Software Engineer (Full‑Stack / Infrastructure) — Frontier AI Evaluation

About The TeamWe build the data, evaluation, and experimentation infrastructure powering next‑generation agentic AI systems. Our work directly supports all five leading AI labs and focuses on the hardest problems in LLM reasoning, RL environments, and human‑in‑the‑loop workflows.We're a fast‑moving, talent‑dense team with backgrounds in quant finance, top‑tier startups, and elite engineering orgs. Revenue is already in the 8‑figure range with a steep growth curve and a major Series A on the way.The RoleThis is a broad, high‑ownership engineering role — not a narrow feature lane.You'll work across research, infra, product, and data, owning systems end‑to‑end. Expect to touch everything from RL environments to distributed infra to full‑stack dashboards.A typical month might include:Prototyping a new RL environment from a research paperDeploying distributed experiments on KubernetesImproving reliability of Next.js dashboardsBuilding a Kafka pipeline for annotator analyticsYou'll shape core systems used by frontier AI labs from day one.What You'll DoBuild scalable systems: RL environments, APIs, human‑in‑the‑loop platformsCollaborate with research, product, and design to ship quicklyWrite clean, maintainable code with strong documentationParticipate in architecture discussions and code reviewsSolve real‑world scalability and reliability challengesContribute to the infrastructure powering frontier AI evaluationWho We're Looking ForWe're looking for early‑career engineers who have already shown they can thrive in fast‑moving, high‑ownership environments and want to work on some of the most challenging problems in AI.Experience1–3 years as a full‑stack software engineerBackground at a high‑growth startup, top quantitative trading firm, or experience as a founding engineer at a company with meaningful early tractionIf your experience is primarily big tech, we look for a strong CS foundation (e.g., top‑tier CS programs such as Berkeley, CMU, MIT, Stanford)Bonus ExperienceTime spent at companies focused on human‑in‑the‑loop AI, data labeling, or AI evaluation (e.g., Surge AI, Snorkel, Scale, Labelbox, Micro1, Mercor)Exposure to fast‑paced environments where you shipped features end‑to‑end and owned outcomesWhat Matters MostYou've built real systems — not just maintained themYou take ownership, move quickly, and enjoy solving hard technical problemsYou're comfortable working directly with researchers, product teams, and customersYou thrive in environments where the roadmap changes based on what you learnTechnical SkillsFull‑stack: Next.js / React, Node.js / PythonInfra: Kubernetes, Kafka, Redis, ElasticsearchAbility to build end‑to‑end systems with high ownershipSoft SkillsStrong ownership and bias toward shippingComfortable being client‑facing with AI lab researchersThrives in fast‑paced, high‑iteration environmentsWork Environment5 days/week onsite in Financial DistrictFlexible hoursOptional half‑day or remote on SundaysTight‑knit, high‑trust, high‑velocity teamWhy JoinWork directly with frontier AI labsSolve the hardest problems in AI evaluationMassive ownership and impact from day oneBuild at a scale most AI startups never reachJoin a team of elite engineers and operators