Live roles

Editor’s noteStrategic AI enablement seat — you own the roadmap, governance, and champion networks that make the rest of Headspace AI-capable, not the AI products themselves.

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 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 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.

Editor’s noteEnablement seat driving AI adoption across a media agency network — heavy on training, rollout, and change management, with ownership of how teams actually use AI tools.

Editor’s noteEmbedded AI enablement role — you build agentic workflows with n8n/Zapier, coach teams on adoption, and own making sure tools actually get used.

Editor’s noteStrategic AI implementation role at a finance consulting firm — you build internal AI tools and prompt libraries, then turn that work into playbooks and SOPs so the whole firm can actually use AI at scale.

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 noteInternship embedding AI adoption across business teams — you train, build playbooks, and translate tools into daily habits for non-technical colleagues. Light on dev.

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

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

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

Editor’s noteEnablement role teaching client teams to keep working with AI through workshops, coaching, plugins, and reusable playbooks.

Editor’s noteBuilds LLM workflows and leaves teams able to run them, prompt engineering and agent debugging included.

Editor’s noteConsultant role building AI playbooks, competency rubrics, and adoption dashboards for GTM and ops teams.

Editor’s noteCX AI role turning service workflows into intents, escalation logic, knowledge systems, and voice/chat automation.

Editor’s noteCustomer-facing deployment role turning LLM capability into report workflows through prompt design and technical guidance, without production code.

Editor’s noteTeaches Claude and ChatGPT at operator depth, building prompt libraries, workflow demos, and role-specific training.

Editor’s noteBuilds internal AI capability through champions, workflow-mapping workshops, and training for no-code agent platforms.

Editor’s noteOwns healthcare agent behavior from concept to rollout, shaping how agents reason across voice, chat, and text.

Editor’s noteCustomer-facing adoption role building champion communities, workshops, and trainer programs around enterprise AI use cases.

Editor’s noteEnterprise enablement manager building AI training, communications, and adoption programs across a large business organization.

Editor’s noteOnboarding leadership role for legaltech customers, more about SaaS implementation teams than hands-on AI workflow craft.

Editor’s noteEarly AI enablement role helping coworkers learn tools, prompts, and use cases across business functions.

Editor’s noteLeads the team turning legal AI onboarding into repeatable playbooks, adoption metrics, and customer change management.

Editor’s noteEmployee enablement role coaching teams on Copilot, prompt patterns, and practical AI use inside day-to-day business work.

Editor’s noteAI enablement role with real LLM workflow work, but the GCP, API, and BigQuery pieces make it more technical.

Editor’s noteTurns enterprise AI rollouts into workshops, champion networks, and trainer programs, heavy on adoption, light on dev.