Live roles

Editor’s noteCross-functional AI adoption role — you're teaching teams to find AI opportunities themselves, not just building tools for them.

Editor’s noteConsulting role getting AI actually used inside German Mittelstand companies — you ship enablement and training, not code, with a real consulting framework backing your work.

Editor’s noteInternal AI product builder role — you ship tools and automations that ~180 people actually use, with AI as your primary building instrument rather than deep engineering.

Editor’s noteGTM ops role that builds and runs AI-powered workflows with Clay, HubSpot, and custom agents — you ship the automation systems, not the product platform.

Editor’s noteInternship building internal AI agents for product ops using vibe coding tools — you're the architect of the workflow and the team's AI translator.

Editor’s noteEnablement role building AI fluency across an ad-tech org — you launch training programs, launch an AI Guild, and own adoption metrics, not the platform.

Editor’s noteEnablement lead role building AI capability across a 10-department org — you own the champion network, skills framework, and training program, with light prototyping when teams get stuck.

Editor’s noteBuilder seat in GTM Operations — you ship AI workflows and agents into production, monitor how they run, and iterate fast. Light on dev, heavy on connecting business needs to working automation.

Editor’s noteEnablement seat getting AI tools actually adopted across teams — you audit workflows, build training, and translate AI for non-technical folks; light on building, partner with tech team for custom solutions.

Editor’s noteEnabling business teams to actually use AI — design sprints, training, and prototyping that transfers capability, not production infrastructure. You build to teach, not to own.

Editor’s noteHands-on AI ops role building and running automation workflows in marketing with Zapier/Make — you ship the automation, not the platform.

Editor’s noteTrust & Safety role building and running AI workflows that flag content, route reports, and handle escalations — you're measured on automation rate and handle time, not on shipping features.

Editor’s noteOperations role configuring and improving Mercury’s customer-facing chatbot and email agents — you monitor performance, expand bot scope, and optimize workflows rather than build the underlying platform.

Editor’s noteStaff-level AI agent PM seat owning enterprise agent behavior and requirements — you define what agents do, not what infrastructure they run on.

Editor’s noteEnablement role bridging AI tools and construction teams — you spend 60-80% on jobsites, coaching PMs and superintendents to actually use the tools, not building the tools themselves. Light on dev, heavy on field work and adoption.

Editor’s noteContract eval/annotation role for AI output quality — you judge whether AI-generated content meets accuracy, cultural, and brand standards, with flexible hours and no coding required.

Editor’s noteEntry-level AI ops seat watching dashboards and logs to catch AI failures before they escalate — you flag and coordinate, engineers do the fixing.

Editor’s noteGTM analyst role where you build AI workflows and enable your team to use them — light on dev, heavy on training and adoption.

Editor’s noteEmbedded AI enablement role in construction tech — you build Claude skills and automations for ops, finance, and sales, then train those teams to own the work after you ship it.

Editor’s noteEmbedding IC role that builds and enables AI capability across business teams — you reimagine workflows with agents and train teams to own them, not hand off to engineering.

Editor’s noteNo-code AI workflow builder shipping automations across sales, support, and ops — n8n, Make, and Zapier are the main tools, Python is a bonus.

Editor’s noteAI adoption and capability-building seat — you identify AI opportunities across business functions, deploy tools with teams, and build the internal frameworks and playbooks for scaling adoption.

Editor’s noteEnterprise AI adoption role at a major apparel brand distributor — you build rollout programs, literacy training, and use-case pipelines, not production AI systems.

Editor’s noteSupport-as-product role where you own the AI workflows that handle tickets — you run escalations, then build the systems that make those escalations.

Editor’s noteDelivery-focused ops role running complex AI implementations inside Fortune 500s — you own program outcomes and client trust, not the engineers doing the building.

Editor’s noteAI adoption role in finance ops — you build learning pathways, playbooks, and champions networks so non-technical employees ship AI prototypes, not production systems.

Editor’s noteEnablement-first AI role in legal tech consulting — you embed in client teams, build integrations and workflows, and drive adoption until AI actually sticks.

Editor’s noteCustomer success role owning AI adoption and capability building across enterprise accounts — you train champions and run workshops, not build product.

Editor’s noteEnablement-focused PM role — you're the AI champion teaching non-technical staff, building training programs, and managing rollout, not engineering AI systems. Light prototyping with Replit/Lovable OK, deep coding not expected.

Editor’s noteHands-on AI builder seat in GTM ops — you ship AI-powered workflows and tools in days, not weeks, using agentic coding tools.

Editor’s noteCustomer-facing AI adoption role helping enterprise clients translate workflows into agentic outcomes — heavy on workshops, prompting, and rollout, light on writing production code.

Editor’s noteRevenue systems lead role that builds and runs AI-powered automations with Clay, Zapier, and n8n — you're owning the GTM tech stack and its workflows, not just advising on it.

Editor’s noteEnablement role driving AI adoption across Jefferies' Equity Research team — heavy on training, hands-on coaching, and low-code tooling, light on dev work.

Editor’s noteRapid-fire builder role using AI coding tools to ship functional code and internal tools — you're generating PRs, not just prototyping.

Editor’s noteApplied AI builder role shipping LLM features, evals, routing, and automation from business need to working prototype.

Editor’s noteAutomation role building agentic workflows across marketing, CRM, and handoffs, with fallbacks and state logic.

Editor’s noteInternal enablement role training teams, finding use cases, and prototyping agent workflows with enough technical depth to be credible.

Editor’s noteConfigures LLM support agents through intent systems, routing logic, retrieval setup, and evaluation loops.

Editor’s noteDeploys agents that clean messy retail catalog data, turning ambiguous product information into working sales workflows.

Editor’s noteEntry-level role building voice agents through conversation design, prompt engineering, and agent behavior translation.

Editor’s noteCustomer-facing agent PM role owning prompt logic, agent design, rollout, and roadmap advice for enterprise deployments.

Editor’s noteInternal AI ops role building tools, prompt libraries, SOPs, and adoption loops across company functions.

Editor’s noteOwns revenue agents like teammates, with scope, metrics, guardrails, and ongoing tuning across GTM workflows.

Editor’s noteConversation design role writing prompts, optimizing chatbot flows, and QA-testing LLM experiences for customer journeys.

Editor’s noteEvaluation role owning RAG and agent quality frameworks, with research-grade Python instead of production infrastructure.

Editor’s noteHealthcare QA role reviewing AI agent calls, catching errors, labeling issues, and improving real workflows.

Editor’s noteOperator seat embedded in revenue, platform, or research work, using frontier AI to tighten execution rhythms.

Editor’s noteOwns production chatbots and AI agents, refining prompts and workflows for support, onboarding, and troubleshooting.

Editor’s noteOwns Claude-powered CX automations, from use-case selection and prompt frameworks to performance monitoring.