GTM Enablement Intern

Aircall.io, Inc.; Paris; On-site; EUR 12,000 - 18,000; Full time

Job summary

Aircall in Paris is seeking a motivated Enablement Intern to join the GTM Enablement team for 6 months. You’ll craft content, manage the Learning Lab and knowledge base ecosystems, and work on an AI Operating Model built on Claude Code.

This role blends enablement fundamentals with AI-driven processes to improve field outcomes. The ideal candidate is pursuing a degree in CS/DS/IS or related fields, comfortable with the command line, and fluent in written English.

Qualifications

• Currently pursuing a degree blending technical and communication skills.
• Strong writing and content design instincts for scannable, useful documentation.
• Comfortable using the command line in daily tasks.
• Basic familiarity with git and version control."
• Excellent written English; the team operates in English.
• Genuine curiosity about AI as a productivity tool and its practical use.
• Structured thinking to break ambiguous problems into steps.

Responsibilities

• Create enablement content and manage Highspot, Confluence, and Learning Lab.
• Operate and extend the AI OS pilot built on Claude Code.
• Draft learning paths, KB audits, and one-pagers from product briefs.
• Document workflows and feed the system’s operational memory.
• Deliver a deployment guide and help scale the AI OS across teams.

Skills

Strong writing

Content design

Degree pursuit

Terminal

Git/version control

Written English

Structured thinking

AI curiosity

Education

Pursuing degree in CS/DS/IS/Web Dev/Digital Communications

Tools

Highspot

Confluence

Notion

Jira

Job description

Aircall is a unicorn, AI-powered customer communications platform used by 22,000+ companies worldwide to drive revenue, resolve issues faster, and scale customer-facing teams. We’re redefining customer communications by bringing voice, SMS, WhatsApp, and AI together into one seamless workspace.

Our momentum comes from a simple idea: help teams work smarter, not harder. Aircall’s AI Voice Agent automates routine calls, AI Assist streamlines post-call work, and AI Assist Pro delivers real-time guidance so people can do their best work. The result is higher revenue, faster resolutions, and teams that scale with confidence.

Aircall is headquartered in Paris, our European HQ, with a strong North American presence anchored in Seattle, our North American HQ, and teams across Madrid, London, Berlin, San Francisco, New York City, Sydney, and Mexico City. We’ve built a product customers love and a business that’s scaling quickly, backed by world‑class investors and driven by rapid AI innovation across multiple product lines.

At Aircall, you’ll join a company in motion. We’re ambitious, product-driven, and execution-focused, with visible impact, fast decisions, and real growth.

How we work at Aircall

We’re customer‑obsessed, data‑driven, and focused on delivering meaningful outcomes. We value ownership, continuous learning, and thoughtful speed. If you thrive in a collaborative, fast‑moving environment where trust and impact matter, you’ll feel at home here.

This is an enablement role first — and an AI role because of it.

You’ll be joining Aircall’s GTM Enablement team at a moment when the function is being rebuilt for an AI‑native world. Day to day, you’ll be doing what great enablement practitioners do: producing content that changes field behaviour, expanding and managing the Aircall Learning Lab, owning the Highspot‑to‑Confluence content ecosystem, and making sure our GTM teams have sharp, current product knowledge at their fingertips.

The AI piece is real — and genuinely unusual — but it serves the enablement mission. We’re piloting a structured AI Operating Model to make the function faster, more consistent, and more scalable. Your job is to help prove it works by doing excellent enablement work with it.

This internship is based in our Aircall Paris office. Duration will be 6 months.

~60% Enablement Delivery

Content creation, Highspot & Confluence management, Aircall Learning Lab, customer adoption programmes, and GTM product knowledge management. This is the foundation

~40% AI OS Pilot

Operate and extend a production AI Operating Model built on Claude Code — because it makes the enablement work better, faster, and more consistent.

Key Enablement Responsibilities (~60%)

• Content Design & Creation

AI Operating Model Pilot (~40%)

This is the part that makes the role unique — but being a unicorn only makes sense on top of excellent enablement fundamentals.

You’ll be embedded in a live experiment: a production AI OS built on Claude Code that gives the enablement function persistent operational memory, deterministic workflows, and a tool ecosystem (Slack, Gmail, Google Calendar, Google Docs, Jira). The experiment only matters if the enablement output improves. That’s the test.

Months 1–2: Learn the System

• Get onboarded onto the existing AI OS instance and shadow core workflows (/scope, /think, /roadmap, /eow)
• Document what works, what’s confusing, and what breaks — from a genuinely fresh perspective
• Start using Claude Code to accelerate your own enablement tasks: content drafting, KB audits, learning path outlines

Months 2–4: Operate and Extend

• Build your own skills for recurring enablement tasks (e.g. “generate a one‑pager from a product brief,” “audit a KB article against the style guide,” “draft a learning path outline from CS call notes”)
• Write context documents that feed the system’s operational memory
• Test skill portability — can a workflow you build be used by a teammate with minimal modification?
• Begin documenting what a team‑wide AI OS looks like vs. a single‑operator one

Months 4–6: Design for Scale

• Tackle the hard multi‑user problems: skill governance, shared vs. personal context, onboarding playbooks, permission models
• Define the measurement framework: how do you prove this produces better enablement outcomes, not just faster ones?
• Produce the primary deliverable: GTM Enablement AI OS Team Deployment Guide, tested with at least one other team member
• Draft the cross‑departmental scaling proposal if successful (what changes going from 6 people to 60?)

Qualifications:

Required

• Strong writing and content design instincts. You take complex information and make it clear, scannable, and useful for a busy field audience. Documentation, tutorials, course content, structured blogs — all counts.
• Currently pursuing a degree in Computer Science, Data Science, Information Systems, Web Development, Digital Communications, or a related field blending technical and communication skills.
• Comfortable in a terminal. You don’t need to be a senior dev, but you shouldn’t be afraid of the command line.
• Basic familiarity with git and version control. Branching, committing, PRs — you’ll work with markdown files in repos.
• Strong written English. The team operates in English; French is a plus for Paris office life.
• Genuine curiosity about AI as a productivity tool, not just a novelty — you should have opinions about how LLMs should and shouldn’t be used.
• Structured thinking. You can break an ambiguous problem into steps and document your reasoning.

Strongly Preferred

• Experience creating instructional or educational content — training materials, e‑learning modules, how‑to guides, technical documentation
• Eye for information design — you notice when a document is hard to scan, when a slide buries the point, when a help article doesn’t answer the question
• Familiarity with Highspot, Confluence, Notion, or similar content management or knowledge management platforms
• Experience with markdown as a working format for real documentation and knowledge management (not just README files)
• Exposure to AI tools (Claude, ChatGPT, Copilot) used seriously for work, not just trivia
• Basic understanding of APIs and integrations — “Claude talks to Slack via an API” should make intuitive sense
• Interest in enablement, education design, or knowledge management — the AI OS is a means; better GTM outcomes are the end
• Any experience with SaaS, B2B, or tech companies, even as a user or in a previous internship

Would be a plus

• Familiarity with LMS platforms or learning experience design (xAPI, SCORM, or equivalent)
• Google Apps Script, Confluence administration, or Jira configuration experience
• YAML familiarity and prompt engineering concepts
• Data analysis skills (Python, SQL, or advanced spreadsheet work) — for measuring content performance or AI OS impact
• Video editing or multimedia content creation experience

What success looks like:

By Month 3

2+ enablement assets shipped and actively used by the field

Highspot content audit complete — migration plan in motion

At least one new Learning Lab module live and tracking engagement

Go‑to person for at least one content domain

Independently using the AI OS for your enablement work

3+ original skills built and usable by teammates

Highspot‑to‑Confluence migration complete — content restructured, not just moved

By Month 6

Learning Lab expanded with

measurable uptick in customer engagement and certifications

GTM KB is current, well‑structured, and actively used by field teams

Customer adoption content in place for at least 2 major product areas

AI OS Team Deployment Guide exists and has been tested

Before/after impact documented on 2+ enablement workflows

What you’ll learn

• Enablement craft. How to design content and programmes that actually change field and customer behaviour — not just materials that tick a box.
• Content ecosystem management. How to run a Highspot‑to‑Confluence migration without losing institutional knowledge or momentum.
• Learning programme design. How to build, launch, and iterate on a Customer and Partner Academy that drives measurable product adoption.
• Knowledge management at scale. Information architecture, content lifecycle, multi‑audience content strategy.
• AI agent system design. How to deploy and govern AI workflows for real business use cases — knowledge that barely exists in the market right now.
• Cross‑functional collaboration. Working across Sales, CS, Product, PMM, and Engineering teams

Why this matters

Most companies are giving employees ChatGPT access and calling it “AI transformation.” That’s not transformation — that’s a search engine with better prose.

The thesis behind this role is that AI becomes dramatically more useful when you give it structured operational memory, deterministic workflows, a tool ecosystem, and the ability to improve its own processes over time. One person has proven this works at Aircall. The question is whether it scales — and whether it produces better enablement outcomes, not just faster ones. That’s what you’re here to answer.

Why join us?

Key moment to join Aircall in terms of growth and opportunities

Our people matter, work‑life balance is important at Aircall

Fast‑learning environment, entrepreneurial and strong team spirit

45+ Nationalities: cosmopolite & multi‑cultural mindset

Competitive salary package & benefits

DE& I Statement:

At Aircall, we believe diversity, equity and inclusion – irrespective of origins, identity, background and orientations – are core to our journey.

We pride ourselves on promoting active inclusion within our business to foster a strong sense of belonging for all. We’re working to create a place filled with diverse people who can enrich and learn from one another. We’re committed to ensuring that everyone not only has a seat at the table but is valued and respected at it by providing equal opportunities to develop and thrive.

We will constantly challenge ourselves to make sure that we live up to our ambitions around diversity, equity and inclusion, and keep this conversation open. Above all else, we understand and acknowledge that we have work to do and much to learn.

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