Product Enablement Manager, AI Agents

Aircall.io•San Francisco, NY

About The Position

Aircall is hiring a Product Enablement Manager for its GTM Enablement team within Customer Solutions & Applied AI. The role focuses on enabling internal teams and customers to adopt and understand Aircall’s AI Voice Agent (AIVA) and AI Messaging Agent (AIMA). It is a new, dedicated role working closely with Forward Deployed Engineering and with Product and Engineering teams responsible for the roadmap. The manager will own how the field learns about each new AI Agent capability, use case, and release. This hands-on, full-stack role combines technical understanding of agentic concepts with the ability to create engaging enablement materials end to end, including writing, filming, and editing video. The role is expected to use AI and agentic tools throughout content production and to develop workflows that help the broader organisation self-serve information and work more efficiently. The position partners with teams across EMEA, AMER, and APAC, including Forward Deployed Engineering, Solutions Engineering, Customer Engineering, Product Support, Number Operations, Product, Engineering, and GTM. It develops scalable launch content and frameworks, maintains current product knowledge, measures enablement effectiveness, and shares field feedback with Product and PMM.

Requirements

2–4+ years of experience in product enablement, technical writing, solutions engineering, forward deployed engineering, content/product marketing, or a similar hybrid role at a SaaS or AI/platform company.
Technical fluency with agentic AI concepts, including prompting, intents, guardrails, and evaluation, and the ability to hold credible technical conversations with Product and Engineering.
Strong written communication and the hands-on ability to script, shoot, and edit video end to end.
Fluent use of AI tools for writing, video and audio generation, editing, and content repurposing; ability to build simple agentic tools or workflows, rather than using AI only as an assistant.
Demonstrated ability to build something from scratch in a fast-moving environment with minimal structure, team, or budget.
Strong stakeholder management across Product, Engineering, Forward Deployed Engineering, and GTM Enablement.
Analytical mindset and experience defining and tracking content or enablement effectiveness, such as usage, time-to-competency, or adoption.

Nice To Haves

Experience at a high-growth AI company or with developer tooling products.
Background in contact centre technology or agentic technology.
Hands-on experience with AI video or audio tools such as Descript, CapCut, Runway, ElevenLabs, Synthesia, or HeyGen.
Experience building lightweight agentic workflows or automations using tools such as Zapier, Make, or n8n.
Prior experience in a formal product enablement, sales enablement, or technical training role.

Responsibilities

Own internal and customer enablement for each AIVA and AIMA launch, translating roadmap items and release notes into playbooks, one-pagers, and videos for relevant teams.
Script, record, and edit feature walkthroughs, demo videos, and explainers about what changed and why it matters.
Use AI tools to draft scripts, generate and edit video and audio, translate and localise content, and repurpose assets into multiple formats.
Build agentic tools and workflows that enable the organisation beyond content, such as internal self-service agents and documentation first-draft generation.
Partner closely with Forward Deployed Engineering to understand field pain points and priorities, and with Product and Engineering to gain early visibility into upcoming releases and prepare enablement plans.
Build reusable frameworks, templates, and video formats to make future launches faster to enable.
Run live launch briefings or office hours when appropriate, while prioritising scalable on-demand content where possible.
Maintain a current, central source of truth for AIVA and AIMA product knowledge in the internal knowledge base or external customer LMS.
Track enablement effectiveness, including content usage, time-to-competency on new features, and internal Q&A volume, and use the data to prioritise future work.
Feed field questions, points of confusion, and knowledge gaps back to Product and PMM.