About

curated AI-native rolesevery role read by a human editornine use cases

What belongs here, and what doesn’t.

A generation of roles exists now that didn’t three years ago: people whose daily work is designing, operating, or shipping agent systems. Most job boards bury them in the same keyword soup as every ML-infra and data-eng role from 2017. We index only the work that’s native to this moment.

Thesis

An AI-native job is one where AI is your primary leverage — not a checkbox skill, not a side benefit. The bar is high on purpose: we’d rather index fewer real roles than pad the board with jobs that merely mention AI.

What is AI-native work?

You’re fluent enough with models, prompts, agents, evals, and the human loop that AI carries most of the work — whether the output is an agent system, a shipped product, campaign output, a faster team, or a tighter workflow. Not “AI experience a plus.” Not “uses ChatGPT at work.” We track nine use cases:

Build Products with AIUse AI coding, no-code, and low-code tools to build apps, websites, MVPs, dashboards, internal tools, directories, marketplaces, prototypes, and digital products.Automate Workflows with AIConnect AI, APIs, and workflow tools to automate repetitive business processes across operations, support, sales, recruiting, finance, and internal teams.Create Content with AIUse generative AI to create content, visuals, video, audio, social assets, ads, explainers, product content, and brand materials.Grow Marketing with AIUse AI to scale marketing, SEO, outbound, lifecycle, lead generation, content pipelines, GTM systems, and campaign operations.Help Teams Adopt AIHelp internal teams become AI-fluent through training, playbooks, workshops, prompt libraries, workflow redesign, and adoption programs.Implement AI for ClientsSet up AI tools, workflows, automations, agents, copilots, and operating systems for clients, customers, agencies, SMBs, or business teams.Test & Improve AI SystemsEvaluate AI outputs for quality, accuracy, usefulness, tone, safety, hallucination, policy compliance, grounding, and reliability.Build AI Products & AgentsBuild AI-native product experiences where AI behavior is central to the product: agents, copilots, assistants, chat interfaces, RAG products, agentic workflows, and model-powered features.Organize Knowledge for AIStructure docs, SOPs, data, knowledge bases, taxonomies, and retrieval workflows so AI systems can answer accurately and work reliably.

Inclusion rule

assertemployer_intent == "explicit"

The employer must say, in their own words, that the role is for applying AI to the actual work type. Not “AI experience a plus.” Not “passionate about AI.” We don’t guess, and we don’t salvage.

What we include

“Founding AI Builder” — posting shows AI-assisted product building
“Design and ship multi-agent workflows for our ops team.”
“Own the planner-executor split for our voice agent.”

“Run the human-in-the-loop layer. Escalate, label, retrain.”
“Break the agent before customers do. Publish evals.”
“Build whatever the agents ask for. No tickets.”

What we reject

“Senior React Engineer · AI-forward team”frontend role with AI in the marketing copy
“Data Scientist — LLMs a plus”classical DS role with keyword sprinkle
“AI Consultant, $200/hr, remote”contract work without employer context

“Prompt engineer for our chatbot”chatbot ≠ agent; no tool use, no loop
“VP, AI Transformation”buzzword layer above the people doing the work
“Looking for AI founders”not a job; a funnel

Not our focus (but fine roles elsewhere)

Classical ML research, model training, core infra, foundation-model safety, and traditional software engineering roles at AI companies all matter — they’re just not what this index is for. This is about the layer where the agent meets the work. For those other roles we suggest ML-specific boards and company pages directly.