AI-DNA Solutions Engineer

IgniteTech; Portugal; Presencial; EUR 50 000 - 70 000; Tempo integral

Resumo da oferta

IgniteTech is seeking a Technical Enablement Engineer who will architect an AI-first enablement system, build prompts and agent workflows, and own knowledge systems for enterprise-scale onboarding and training. You will run demos, create engaging training materials, and maintain content aligned with product releases.

The role emphasizes autonomous AI-driven enablement with limited human intervention, demanding strong stakeholder communication and hands-on experience with enterprise platforms.

Qualificações

• 3+ years in enterprise community engagement or social media management platforms.
• Proven customer-facing experience with live demos and onboarding.
• Ability to verify AI-produced deliverables against the live product.
• Strong product sense and writing quality.
• Frontier AI fluency with agents and tooling.
• Ownership mindset and proactive approach.

Responsabilidades

• Onboard enterprise customers onto community engagement and social media management products, running structured sessions to deliver value quickly.
• Prepare and deliver product demos for clients, prospects, and executives, including environments, storylines, dry runs, and real-time feature coverage.
• Own documentation and training across the product family, updating within days of releases using AI-driven workflows.
• Design and improve the AI-native system core: prompts, skills, knowledge bases, and feedback loops for autonomous enablement work.
• Turn customer signals into reusable resources and structured product feedback to accelerate the team.
• Maintain demo-readiness across product family with updated environments and data sets.
• Provide structured async updates: daily logs and weekly goal reviews with demos.

Conhecimentos

AI-native mindset

Enterprise enablement

Public speaking

Customer onboarding

Demo delivery

Descrição da oferta de emprego

Build the System. Let AI Do the Work. Own the Result.

We're looking for a Technical Enablement Engineer who operates AI-first by default - someone who builds the prompts, agent workflows, and knowledge systems that let AI own enablement at enterprise scale, then verifies and ships what comes out. You'll be the person Fortune 100 brands meet during onboarding, demos, and training - backed by AI agents you design and direct.

This isn't a traditional enablement seat. There's no hand-writing docs, no recycling slide decks, no sitting in a loop with a chatbot. You architect the system; the system does the production. One person plus their agents, delivering what used to take a full team.

What You'll Do

• Onboard enterprise customers onto community engagement and social media management products - running structured sessions that get users to value fast, with each cohort benefiting from a smarter, faster system you continuously refine.
• Deliver and prepare product demos for clients, prospects, and executive audiences alongside product leadership - including demo environments, storylines, dry runs, and real-time coverage of new features.
• Own documentation and training across the product family, keeping everything current within days of each release using AI agents and verification workflows you build yourself.
• Design and improve the AI-native system at the core of the role - the prompts, skills, context, knowledge bases, and feedback loops that let agents autonomously produce enablement work with less human intervention over time.
• Turn customer signals into leverage - recurring questions become self-serve resources, onboarding friction becomes structured product feedback, and every improvement is shared so the whole team accelerates.
• Maintain demo-readiness - environments, data sets, talk tracks, and storylines kept sharp across the full product family.
• Deliver structured async updates - daily check-ins, work logs, and weekly goal reports with demos.

What We're Looking For

• AI-native operator. You don't treat AI as a side tool - you build the context, examples, and guardrails that let agents own work end-to-end. You direct, verify, and get out of the way.
• 3+ years in enterprise community engagement or social media management platforms - hands-on with managing, administering, onboarding, or enabling users on these products.
• Proven customer-facing chops. You've run live demos, trainings, or onboarding for enterprise buyers. You're clear, confident, and credible in front of a Fortune 100 room - composed next to an SVP.
• Closed-loop quality discipline. You verify every AI-produced deliverable against the live product. No hallucinated steps, no stale screenshots, no "good enough."
• Strong product sense and writing quality. Product leadership can hand you a goal - not a spec - and trust what you deliver will be polished and audience-appropriate.
• Frontier AI fluency. You delegate real work to agents, you're never locked to one tool, and you have sharp, current judgment on which model fits which task.
• Ownership mindset. Mission-driven, self-directed, proactive on the boring stuff too. You treat blockers as puzzles, not escalation tickets.

Bonus Points

• Admin-level experience running an enterprise community or social platform instance.
• Background in instructional design, technical writing, or curriculum development.
• Video production skills for walkthroughs and training content.
• Prior solutions engineering or sales engineering experience.
• Hands-on building AI assistants, chatbots over knowledge bases, or contributing to shared prompt/skill libraries.

Why This Role Compounds

You'll sit at the intersection of enterprise enablement, applied AI systems, and customer success for major brands. The real growth here is in the skill that matters most right now: building durable leverage - prompts, agent workflows, knowledge systems - that lets AI own more of the work over time, and sharing it so an entire team gets faster.

The AI-native way of working is already in production here. No token limits. No tooling restrictions. If the right answer is a better model, a new agent config, or a tool that isn't in the stack yet, that conversation is always open. You'll help define what "forward deployed" looks like in the AI era.