Sales AI Enablement Associate

Groupon•Chicago, IL

16h•Hybrid

About The Position

Groupon is rebuilding its sales motion with AI at the centre. Project Foundry's autonomous agent fleet handles the outbound motion, ranks the queue through predictive intelligence, and brings warm leads to the rep's desk. That fleet is running. The question now is what happens at the handoff — the quality of what reps do with the intelligence Foundry delivers is what determines whether it converts. The Sales AI Enablement Associate exists to close that gap... This is not a training role. The existing onboarding function handles live delivery and new hire ramp. This role owns the content infrastructure behind it — what gets built, how it’s informed by data, and how it improves continuously as rep performance signals change. You report directly to the CSO and work at the intersection of AI, data, and commercial execution.

Requirements

A degree from an Ivy League or equivalent top-tier university strongly preferred — communications, education technology, data science, psychology, or any field that trained you to translate complex information into clear, actionable content.
Up to 2 years of professional experience.
Demonstrated ability to create content using AI tools — you have used LLMs to generate, structure, and refine learning or enablement material, and you know how to apply judgment to the output rather than accepting it wholesale.
Data literacy strong enough to read a Salesforce report and draw a content conclusion — you don’t need to be a data scientist, but you need to be comfortable sitting in a dataset and extracting a signal.
Strong written and verbal communication — the content you build needs to land with a rep who has 30 seconds between calls. You write for that person, not for a slide deck reviewer.
Intellectual curiosity about how people learn and what makes commercial training actually stick — not theory, but a genuine instinct for what works in a fast-moving sales environment.

Responsibilities

Own the AI-powered content library — Design and build the enablement content reps use to work leads, handle objections, and close deals. Every asset is AI-assisted, data-informed, and built to be updated as performance signals evolve — not a static deck that ages out in three months.
Mine sales data to identify capability gaps — Pull signal from Salesforce, Salted CX, and call data to understand where rep performance breaks down. Turn that into a prioritised content roadmap. You don’t guess what reps need — you read it in the data.
Iterate content based on performance outcomes — Track whether content actually changes behaviour. If conversion doesn’t move after a module goes live, you go back into the data, find out why, and rebuild. Every asset has a before/after record.
Embed AI tools into the sales workflow — Identify where AI can reduce rep effort or sharpen rep judgment — call prep, objection handling, pitch sequencing — and build the content that makes adoption practical and sticky.
Build for scale, not for yourself — Everything you create can be updated, used, and adapted by a rep or manager without your direct involvement. You are building a system, not running a program.