# AI-Native JD Benchmark — Knowledge Base for the Gem **Purpose:** Ground the "JD AI-Native Check" Gem on *real* job descriptions, not just model memory. Attach this file to the Gem's Knowledge so its gap analysis and benchmark refs quote actual AI-native phrasing. **Source:** Public ATS scrape (Greenhouse, Lever, Ashby) of 34 frontier AI companies — 3,497 open roles, 120 HR/People/TA roles. Snapshot May 29, 2026. Companies include Anthropic, OpenAI, Scale AI, xAI, Cohere, Harvey, Notion, LangChain, Glean, ElevenLabs, Decagon, Mistral, Sierra, Together AI, Cursor, Mercor. > **How the Gem should use this:** When analyzing a JD, compare it against the patterns and > real quotes below. In BENCHMARK REFS, lift or adapt actual phrasings from the "Real > phrasings" section and cite the company. Flag where the JD lacks the markers in > "What makes a JD AI-native." --- ## The three structural shifts (what AI-native hiring looks like now) 1. **AI fluency is now an explicit requirement, not a perk.** ~46% of HR JDs at these companies require it (was ~0% three years ago). Fluency means agents, evals, RLHF, AI tooling — not "comfort with HR tech." 2. **"Recruiter" has split into six parallel variants:** Technical Recruiter (AI/ML Research), GTM Recruiter, Executive Recruiter (International), Technical Sourcer, Multi-region Coordinator, Recruiting Optimization Manager. 3. **People is being rebuilt as an analytics-driven, full-stack function:** Head of People Science (OpenAI), People Programs + Total Rewards Architect (LangChain), Workforce Planning Lead (Anthropic), Compensation Business Partner (OpenAI). --- ## What makes a JD AI-native (the benchmark checklist) - **Outcome-framed**, not task lists — "own the outcomes end-to-end," "define success metrics." - **AI as leverage the person wields** — expected to automate the tactical to free up judgment work. - **AI fluency stated as baseline** in qualifications, with specifics (agents, evals, tooling). - **Comfort with ambiguity / 0-to-1 / "build role"** language — invent the playbook, not execute one. - **Broader scope, smaller team** — "founding," "high-autonomy," end-to-end ownership. - **Judgment, taste, ownership** prized over years-of-tool-X. - **Velocity** — "ship fast," "decision velocity," "experimentation throughput." If a JD is missing 3+ of these, it lags the AI-native standard. --- ## AI-native vocabulary (frequency signal from 2026 HR JDs) Most common markers, by how often they appear: **Agentic / AI agent** (most frequent), **Frontier / frontier lab**, **AI tooling in HR**, **Evaluation / Evals**, **0-to-1 / Founding**, **Hypergrowth**, **LLM / Foundation model**, **Async / Distributed**. A traditional JD will have none of these. An AI-native one will have several, used concretely (not as decoration). --- ## Real phrasings to lift or adapt (quoted from actual JDs) **On AI as the work itself** - *"Your goal is to automate and leverage agents to handle the tactical … so you can focus on the complex underlying strategy, philosophy, and change management."* — LangChain, People Programs & Total Rewards Architect - *"Use our own tech stack to automate the 'ops' out of People Ops."* — LangChain - *"Deploying automation (n8n, AI tooling, custom integrations) wherever it meaningfully reduces friction."* — ElevenLabs, Talent Operations Lead - *"Be a builder: design and ship the systems that power total rewards operations … to automate workflows, improve data quality, and increase decision velocity."* — Notion, Head of Total Rewards **On AI fluency as a baseline** - *"AI Fluency: You aren't just a user of AI; you are an enthusiast."* — LangChain - *"AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work."* — Glean, HRBP - *"You're curious and willing to adopt AI tools to work smarter and deliver better results. For some roles, AI fluency is a core requirement — when that's the case, we'll make it explicit."* — Notion, People Ops Generalist - *"You enjoy staying current on AI tools and finding creative ways to integrate them across your work."* — Scale AI, Business Recruiter **On outcomes over tasks** - *"Set the vision for Total Rewards as a talent-density lever … and own the outcomes end-to-end."* — Notion - *"Define success metrics for operational quality, employee experience, experimentation throughput, and impact on business outcomes."* — OpenAI, Head of People Science - *"Connect people strategy to business outcomes."* — Harvey, PBP **On ambiguity, 0-to-1, build-roles** - *"This is a build role … invent the playbook rather than execute someone else's. Suits someone energized by extreme ambiguity, ships fast."* — Anthropic, Lead Talent Development - *"Comfortable in the messy middle of hyper-growth and can navigate ambiguity with a technical mindset."* — LangChain - *"A track record of turning ambiguity into structure."* — Harvey, PBP - *"High-impact, high-autonomy role … influencing hiring outcomes."* — Decagon, Senior Technical Sourcer --- ## New role archetypes (with real source URLs) - **Talent Development & Enablement** — Anthropic: https://job-boards.greenhouse.io/anthropic/jobs/5207861008 - **Specialized Technical Recruiter (AI/ML)** — Together AI: https://job-boards.greenhouse.io/togetherai/jobs/5135941007 · Decagon: https://jobs.ashbyhq.com/decagon/9efceeb7-9c23-481d-84c2-7c7fa1f59ef9 - **Talent Operations Lead** — ElevenLabs: https://jobs.ashbyhq.com/elevenlabs/da8e86bb-f9a7-4d6c-8699-e2e11779915e - **Head of People Science** — OpenAI: https://jobs.ashbyhq.com/openai/794e6d74-1ab1-459d-8adb-bb3398e9deb1 - **People Programs + Total Rewards Architect** — LangChain: https://jobs.ashbyhq.com/langchain/ff53c1cd-830e-4e18-b6fe-9e69b3cf4f57 - **Compensation Business Partner** — OpenAI: https://jobs.ashbyhq.com/openai/c96e7e29-5da5-4f90-b80d-c3c59f0ab0f4 - **Recruiting Optimization Manager** — OpenAI: https://jobs.ashbyhq.com/openai/2fc08730-bed0-4273-91ec-78c17f43f500 - **Executive Recruiter (International)** — OpenAI: https://jobs.ashbyhq.com/openai/0bab3f42-5290-41ec-b9b5-0de22f2404f6 --- ## Comp anchors (frontier-lab recruiting, USD) - Talent Associate (Decagon, 2025): $100k–$130k - Senior Technical Sourcer (Decagon): $140k–$200k - Senior Technical Recruiter (Decagon): $180k–$240k - Recruiting Optimization Manager (OpenAI): $216k–$240k Use these as a reality check: AI-native technical recruiting roles command a premium and are scoped with far more autonomy than a standard coordinator role. --- ## Geo caveat (be honest about this) The reinvention is heavily a North America story (~76% of HR roles). EMEA + APAC AI labs are still largely hiring plain Recruiters + HRBPs + People Ops. Partly real, partly an artifact of which companies expose public ATS APIs. Don't over-apply the "everything has changed" framing to non-US roles.