Live roles

Editor’s noteEnablement role driving AI adoption across business teams — heavy on use-case mapping, workflow design, and change management, not implementation.

Editor’s noteEnablement seat building AI capability across business teams — you run pilots and build playbooks, not own a product or operate live agent workflows.

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 noteSystems ownership role for Pigment (financial planning) with AI adoption work across Finance — moderate coding via SQL and integrations, but core work is running and scaling AI-enhanced finance workflows.

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 noteGTM automation role — you build and run enrichment pipelines and outbound workflows across Clay, Zapier, and AI tools, with measurable impact on sales team productivity.

Editor’s notePart-time contractor seat contributing senior ops expertise to AI training data — you design real-world tasks and evaluate how AI handles operations scenarios.

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 noteAI adoption role embedded in construction field ops — you coach jobsite teams on AI tools, translate capabilities into construction language, and feed field intelligence back into what gets built next.

Editor’s noteOps role running AI workflows in a post-sales org — you build automations in Workato and configure them in Salesforce/Gainsight/Zendesk, not write production code.

Editor’s noteOwn the systems and metrics that determine whether AI models actually work in the real world—golden sets, eval pipelines, accuracy SLAs, and automated QA.

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 noteEnablement role scaling AI adoption across an edtech company — you build the playbooks, prompts, and training, not the platform. Light on dev, heavy on making teams actually use AI day-to-day.

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

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 noteForce-multiplier ops role applying AI tools like Zapier and ChatGPT to automate internal workflows at a science-AI startup — you own operational systems, not the AI platform itself.

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 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 noteEarly-stage AI voice agent startup looking for someone to build and run the operational systems that scale their platform to $100M ARR.

Editor’s noteEnablement seat translating attorney needs into AI-assisted workflows — you train, support, and maintain the use-case library, not the infrastructure.

Editor’s noteOperations role building and tuning AI workflows with Make, Airtable, and LLMs — you ship the automation, not the platform.

Editor’s noteAdoption role embedding AI into humanitarian operations — you diagnose workflows, build reusable assets, and coach teams until they don't need you.

Editor’s noteEnablement role running an internal AI champions program — you teach people to use AI tools, not build them.

Editor’s noteEarly-career ops seat building and managing AI agents for marketing campaigns — you ship automation across B2C/B2B workflows, light on dev for a product builder.

Editor’s noteAI adoption lead role at a humanitarian org — the title suggests heavy enablement and workflow integration work, but the actual description content was missing from the scrape.

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

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