Live roles

Editor’s noteGrowth PM seat on a high-converting AI B2C SaaS — you own acquisition, activation, and retention end-to-end, with daily AI prototyping via Claude Code for production concepts.

Editor’s noteSenior automation role — you build AI-powered GTM workflows at scale, but Marketo architecture, Salesforce routing, and SQL are the real core work, with AI tooling layered on top.

Editor’s noteOwn the full PLG loop for an AI-focused product using Clay, n8n, and LLMs — you ship growth agents, not a marketing roadmap.

Editor’s noteAI-native operator building and shipping internal AI agents and lightweight apps across recruiting, finance, and sales — you own the whole loop from spec to observability.

Editor’s noteProduct builder role that blends PM instinct, design thinking, and TypeScript coding — AI fluency is table stakes, but this leans engineering-heavy and asks you to own full product arcs end-to-end.

Editor’s notePrototyper role at Mondadori's AI accelerator — you build and ship AI experiments fast, no IT backlog, vibe coding with Cursor/Replit/Bolt expected.

Editor’s noteStaff PM seat owning a major consumer surface end-to-end — you also model what AI-native PM craft looks like, ship prototypes with AI tools, and raise the bar for the function.

Editor’s noteSystems-builder role inside the Office of the CEO — you ship AI agents and internal tools, not production software, using vibe-coding and lightweight infrastructure work.

Editor’s notePM role owning agent fleet product and chat flow evals — prototype fast with AI tools, run 15-20 user sessions weekly, decide what ships.

Editor’s notePM role defining and shipping multi-agent AI systems at massive scale — you own AI product direction, not backend engineering, and prototype with vibe coding tools rather than writing production code.

Editor’s notePM role shipping LLM-powered features (agents, RAG, intelligent assistants) on a sustainability platform — vibe-code your own prototypes, set eval criteria, and own what gets built.

Editor’s noteAdoption role at an energy company scaling AI tools across teams — you drive capability, not code; light on dev, heavy on coaching and rollout.

Editor’s noteEnablement-heavy AI builder role — you build agents and workflows while driving enterprise-wide adoption through training, champions networks, and prompt libraries.

Editor’s noteEnablement lead role building AI capability across a biotech ecosystem — hands-on coaching, training programs, change champion networks, and tool adoption; light on dev work.

Editor’s noteOwns AI support infrastructure from the ground up — you deploy agents, build the knowledge base that retrieves against, then automate ticket flows so the team stays lean.

Editor’s noteSenior AI enablement role building company-wide AI fluency through training programs, community of practice, and cross-functional capability building — you grow the org's AI muscle, not own production workflows.

Editor’s noteInternal AI transformation lead role — you own how the whole company adopts AI, from hands-on prototyping with RAG and lightweight agents to driving adoption across GTM, Services, and Finance.

Editor’s noteOps role building and deploying AI automations for client briefs using n8n, Zapier, and Claude Code — you ship the workflow, not the platform.

Editor’s noteOperations role building and tuning AI automations for sales and internal workflows — you ship the automation, not the platform. Light on coding, heavy on running things.

Editor’s noteCoaching and change-management role in construction that gets employees actually using AI tools — no AI system building required, heavy on 1:1 enablement and training delivery.

Editor’s noteOperations role managing AI agent deployments into enterprise financial environments — you keep the workflows running, handle escalations, and improve the playbooks, not the code.

Editor’s noteAI adoption and process change role — you build the framework, playbooks, and training that help teams across the company use AI tools responsibly.

Editor’s noteSenior architect role shipping AI solutions for government and enterprise clients using vibe coding and agentic IDEs — you build the proof-of-concept, not the platform.

Editor’s noteProduct-builder seat using AI coding tools to ship SaaS features end-to-end — you're generating the code and shipping the product, not owning the platform.

Editor’s noteGrowth marketer seat where you build and run AI agent workflows for content, paid, and distribution — one-person output at 10-person scale, minimal traditional marketing ops.

Editor’s noteProduct Builder role defining agent analytics as a category—you prototype with AI tools, ship working software, and own strategy end-to-end, not just specs and handoffs.

Editor’s noteImplementation-focused CSM role where you deploy Glean's AI platform for enterprise customers — heavy on project management, SSO/connector setup, and adoption monitoring.

Editor’s noteOperations-focused AI role owning end-to-end agentic workflows in production — you monitor, tune, and iterate the workflows, not the platform underneath.

Editor’s noteAI-native PM role — you own 0-to-1 product building end-to-end using vibe-coding tools, then hand off to engineering for scaling.

Editor’s noteInternal AI coach and automation lead role — you build agents and workflows across the whole company, but the win condition is teams becoming more AI-fluent, not shipped product features.

Editor’s noteEnablement role connecting AI capabilities to teams — you build and deploy MCP tool bundles, then measure success by whether teams actually use what you ship.

Editor’s noteOwn AI workflow delivery and quality for pharma customers — you ship the workflow and iterate prompts with the AI team, not build the platform.

Editor’s noteIT support role focused on troubleshooting AI tools like Copilot, Glean, and ChatGPT across a financial consulting firm — you're the escalation point, not the builder.

Editor’s noteOwn the Self-Service Ecosystem end-to-end — prototype AI workflows, tune knowledge bases for LLM retrieval, and measure deflection. You're the bridge between support ops and AI tooling, not a platform engineer.

Editor’s noteOps seat building and owning AI workflows that automate executive operations — you ship production agents weekly, not platforms or products.

Editor’s notePM seat owning agent behavior end-to-end — you define how AI agents reason, interpret intent, and execute workflows, then measure whether they actually work.

Editor’s noteEnablement seat embedding AI capability across an investment firm's business units — you build teams' AI skills and reusable patterns, not the platform itself.

Editor’s noteRuns and quality-checks AI-driven medical workflows for US clinics — you own the outputs, tweak prompts, and escalate to engineers when needed, not when you can fix it yourself.

Editor’s noteAI enablement role in healthcare AI — you grow how other teams use AI through tooling, training, and champions programs, not by owning production engineering.

Editor’s noteRuns and scales AI workflows across sales, CS, and ops — you ship the agent, then own keeping it reliable in production.

Editor’s noteTrainer role at Dr. Ng's advisory firm — you translate deep AI concepts (RAG, evals, agents) into executive-ready workshops and curriculum, light on coding, heavy on teaching.

Editor’s noteEnablement role embedding with enterprise clients to change how teams work with agentic tools — you teach, train, and scale adoption, not build the tools themselves.

Editor’s noteEnablement-focused director role at a B2B e-commerce company — you grow people's AI capabilities, not build AI systems. Heavy on change management and literacy.

Editor’s noteOwns AI adoption and training across the whole org — you build the roadmap, audit workflows, and upskill teams; the tech team does the actual building.

Editor’s noteSenior AI product seat shaping Generative AI features across financial product suites — you ship AI capabilities, lead a team, and talk to senior leadership, not write production code.

Editor’s noteHands-on AI ops role running and scaling Ramp's customer-facing agentic workflows — you ship the automation and own how it performs week-to-week, not build the platform.

Editor’s noteEnablement-first role coaching Sales and Ops teams on AI tools — you configure agents and workflows, but your real job is making people actually adopt them.

Editor’s noteSupervise live AI agents in a call center context — step in when agents stumble, catch failure patterns, and feed what you learn back to the team. Light on dev, heavy on judgment and real-time oversight.

Editor’s noteCustomer-facing adoption role — you help enterprises actually use Writer's AI tools at scale through training, playbooks, and workflow mapping, not build the platform itself.