IgniteTech
Website:
ignitetech.com
Job details:
Hook
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.
What you will be doing
- 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. This is the heart of the role.
- 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.
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.
Responsibilities
- 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.
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.
Click on Apply to know more.
