› Customer success role owning AI adoption and capability building across enterprise accounts — you train champions and run workshops, not build product.

› Enablement-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.

› Hands-on AI builder seat in GTM ops — you ship AI-powered workflows and tools in days, not weeks, using agentic coding tools.

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

› Revenue 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.

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

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

› Applied AI builder role shipping LLM features, evals, routing, and automation from business need to working prototype.

› Automation role building agentic workflows across marketing, CRM, and handoffs, with fallbacks and state logic.

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

› Configures LLM support agents through intent systems, routing logic, retrieval setup, and evaluation loops.

› Deploys agents that clean messy retail catalog data, turning ambiguous product information into working sales workflows.

› Entry-level role building voice agents through conversation design, prompt engineering, and agent behavior translation.

› Customer-facing agent PM role owning prompt logic, agent design, rollout, and roadmap advice for enterprise deployments.

› Internal AI ops role building tools, prompt libraries, SOPs, and adoption loops across company functions.

› Owns revenue agents like teammates, with scope, metrics, guardrails, and ongoing tuning across GTM workflows.

› Conversation design role writing prompts, optimizing chatbot flows, and QA-testing LLM experiences for customer journeys.

› Evaluation role owning RAG and agent quality frameworks, with research-grade Python instead of production infrastructure.

› Healthcare QA role reviewing AI agent calls, catching errors, labeling issues, and improving real workflows.

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

› Owns production chatbots and AI agents, refining prompts and workflows for support, onboarding, and troubleshooting.

› Owns Claude-powered CX automations, from use-case selection and prompt frameworks to performance monitoring.

› Enablement role teaching client teams to keep working with AI through workshops, coaching, plugins, and reusable playbooks.

› Builds and operates AI workflows for GTM teams, combining agents, automation, systems integrations, and human review.

› Builds LLM workflows and leaves teams able to run them, prompt engineering and agent debugging included.

› Consultant role building AI playbooks, competency rubrics, and adoption dashboards for GTM and ops teams.

› CX AI role turning service workflows into intents, escalation logic, knowledge systems, and voice/chat automation.

› QA role reviewing AI support conversations for accuracy, policy fit, tone, and recurring failure patterns.

› Customer-facing deployment role turning LLM capability into report workflows through prompt design and technical guidance, without production code.

› Creative production role using Midjourney, Stable Diffusion, ComfyUI, and prompt iteration to make client-ready visuals.

› Daily agent ops role building, monitoring, debugging, and tuning conversational AI workflows across enterprise use cases.

› Shapes AI personality, tone, prompts, and guardrails for conversational systems, more behavior design than flowchart work.

› Red-team role finding jailbreaks, ranking model failures, and documenting attack paths so safety teams can patch them.

› Builds and runs AI automations with Claude, n8n, and similar tools, shipping practical workflow fixes fast.

› Teaches Claude and ChatGPT at operator depth, building prompt libraries, workflow demos, and role-specific training.

› Builds internal AI capability through champions, workflow-mapping workshops, and training for no-code agent platforms.

› AI product role taking agent features from concept to launch, with workflow tuning and interface design in the mix.

› Owns healthcare agent behavior from concept to rollout, shaping how agents reason across voice, chat, and text.

› Customer-facing adoption role building champion communities, workshops, and trainer programs around enterprise AI use cases.

› Enterprise enablement manager building AI training, communications, and adoption programs across a large business organization.

› Onboarding leadership role for legaltech customers, more about SaaS implementation teams than hands-on AI workflow craft.

› Creative pipeline architecture role building AI workflow systems and scripts, more technical than most operator seats.

› Early AI enablement role helping coworkers learn tools, prompts, and use cases across business functions.

› Leads the team turning legal AI onboarding into repeatable playbooks, adoption metrics, and customer change management.

› Real estate AI transformation role building prompt libraries, workshops, and champion programs for non-technical teams.

› AI Enablement, Recruiting ops role rebuilding scheduling, follow-ups, dashboards, and candidate workflows with AI agents and low-code tools.

› Employee enablement role coaching teams on Copilot, prompt patterns, and practical AI use inside day-to-day business work.

› AI enablement role with real LLM workflow work, but the GCP, API, and BigQuery pieces make it more technical.

› Prompt systems role testing outputs, tightening schemas, and maintaining reusable prompt frameworks, no software engineering background required.

› Healthcare agent ops role deploying and tuning clinical workflows, with foundation model APIs and monitoring in the loop.