AI-DNA Sales Engineer

About the role

This role is forward deployed at the frontier of AI-native customer work, where you are the person Fortune 100 brands meet at the moments that matter most, backed by AI agents you build and direct.

Responsibilities

• Onboard enterprise customers and users onto community engagement and social media management products — structured sessions that get admins, moderators, and everyday users to first value fast, with each cohort onboarding faster than the last because the system you build absorbs what you learn.
• Run product demos for clients and prospects, and prepare and support executive demos alongside product leadership — demo environments, storylines, dry runs, and same-day coverage of newly shipped capabilities.
• Own the documentation and training materials across the product family — kept current with every release through AI agents and workflows you build, verified against the live product.
• Build and continuously sharpen the system that lets AI own the work — the prompts, skills, context, knowledge bases, and verification loops that let agents produce whole classes of enablement work autonomously, so each class needs less human intervention over time.
• Turn what you hear into leverage: recurring questions become self-serve assets, onboarding friction becomes product feedback, and every fix is shared so the whole team benefits.
• Make every customer touchpoint — onboarding, demos, documentation, and training — enterprise-grade, accurate, and always current, at a speed and volume only an AI-native operator can sustain.
• Relentlessly remove the bottlenecks that keep AI agents from owning enablement work end to end, so one person (plus their agents) delivers what a traditional enablement team many times the size would.
• Leave durable, shared leverage behind every cycle: prompts, skills, context files, and agent workflows contributed to shared repos.
• Funnel voice-of-customer findings from onboarding and demos to product leadership as structured input.
• Maintain demo environments, demo data, storylines, and talk tracks demo-ready across the product family.
• Ship documentation updates within days of each product release, verified against the live product.
• Keep living knowledge bases current, feeding the AI assistants and agents that answer and produce.
• Deliver async deliverables: daily check-ins, work-log updates, and weekly goal reports with demos.

What you will NOT be doing

• Hand-writing documentation, hand-building decks, or sitting in 1:1 loops with an AI assistant. AI does the production; you build the system that lets it, and you own the result.
• Reading from someone else's script. You know the products cold, you build the demo, and you're trusted in the room.
• Waiting for creative briefs or detailed specs. You're handed a goal — a customer to onboard, a demo to land, a release to cover — and trusted to figure out the right way to deliver it, polished.
• Answering the same question twice. If it cost a human answer this week, you make it self-serve for next time — you don't grind through it again.
• Settling on one tool. You operate at the frontier, daily, and you're always testing what's next.
• Treating "sent" or "the demo worked" as "done." Done is accurate, current, polished, and adopted — material a Fortune 100 brand can rely on.

Requirements

• AI-DNA — it's how you operate, not a tool you reach for. You don't hand-produce enablement work or sit in 1:1 loops with an assistant. Your default is to get out of the AI's way: build the context, examples, and guardrails that let agents own work end-to-end, then direct and verify.
• 3+ years of hands-on professional experience with enterprise community engagement and/or social media management platforms — managing, administering, onboarding, or enabling their users.
• Demonstrated customer-facing experience: live demos, trainings, or onboarding sessions for enterprise customers, delivered in clear, confident spoken English. Credible in front of a Fortune 100 audience and composed alongside an SVP.
• Closed-loop accuracy discipline — you verify AI-produced material against the live product and build checks agents run on themselves. You don't ship hallucinated steps or stale screenshots.
• Strong product taste and writing quality — polished docs, considered training, demos built around the audience. Product leadership can hand you a goal, not a spec, and trust what comes back.
• Heavy, advanced use of today's frontier AI tools — delegating real units of work to agents, never locked to one tool, constantly experimenting.
• Sharp, current model judgment — which model for which task, and what changed across recent releases.
• Ownership and proactiveness — mission-driven, no babysitting required, even on the boring tasks. Treats blockers as challenges to overcome, not problems to escalate.
• Enterprise customer experience — you've worked with large, demanding organizations and understand what their scrutiny means for everything you show and ship.

Nice to Have

• Administrator-level experience with an enterprise community or social media management platform (running the instance, not just using it).
• Instructional design, technical writing, or curriculum development background.
• Video production for product walkthroughs and training.
• Prior forward-deployed, solutions engineering, or sales engineering experience.
• Experience building AI assistants or chatbots over knowledge bases, or contributing to shared prompt/skill libraries.

What you will learn

You'll operate at the frontier of AI-native customer work — a live cross-section of enterprise enablement, applied AI systems, and the craft of making Fortune 100 customers successful. You'll develop a rare depth in the thing that actually compounds: building the leverage that lets AI own more of the work, and sharing it so a whole team gets faster. The AI-native way of working here is already in production — you'll help define what "forward deployed" means in the AI era. No token limits. No tooling limits. If the right answer is a better model, a different agent configuration, or a tool not yet in the stack, that conversation is always open.