[Hiring] Customer Success Manager @Sportsdigita

Role Description

We are rebuilding Customer Success from the ground up and we are building it for how software actually works now. This isn't a ticket queue with a friendly voice on top. We are standing up a team where AI does the repetitive work and humans do the work that changes outcomes: sharp onboarding, real training, early reads on account health, and the kind of day-to-day partnership that makes renewal the obvious decision.

You will be one of the first people in that model. You will use AI daily, not as a novelty, but as the way the job gets done. You will sit close enough to the product to influence it. And you will own the customer relationships that determine whether this company grows.

If you are the kind of person who has already rewired your own workflow with AI because the old way was too slow, this role will fit you.

What You Will Do

• Customer Experience & Response
  • Use AI to accelerate the queue: draft responses, summarize long threads, cluster recurring issues, and turn resolved tickets into reusable answers.
  • Hold a high bar on quality. AI drafts it; you own it. Every response goes out clear, accurate, and on-brand.
  • Treat the knowledge base as a living product, not a graveyard. If a question comes in twice, it becomes self-serve.
  • Own the customer success inbox — triage fast, answer what you can, escalate what needs product or engineering, and route the rest.
• Onboarding & Enablement
  • Run onboarding for new customers — kickoff, configuration, first-value guidance, and the follow-through that makes it stick.
  • Deliver product training 1:1 and in group sessions, including our AI capabilities. You will need to explain what the technology does, where it helps, and where it doesn't.
  • Build and maintain training materials, walkthroughs, and customer-facing documentation — and use AI to keep them current as the product ships.
  • Spot the accounts that aren't adopting and get to them before the pattern hardens.
• Project Coordination
  • Manage customer-facing projects end to end — timelines, milestones, status, delivery.
  • Coordinate across product, engineering, and design to get customers what they need, on schedule.
  • Communicate proactively: what's happening, what's next, what's blocked, and when it clears.
• Product Partnership
  • Be the signal path from the field to the roadmap. What customers are struggling with, asking for, and working around should reach product through you — structured, prioritized, and evidence-backed.
  • Pressure-test new features before they ship and help shape how they're rolled out.
  • Bring an opinion. We'd rather have a CSM who argues for the customer than one who files the request and moves on.
• Customer Health & Revenue Partnership
  • Work from data, not vibes. Usage trends, engagement patterns, and product signals should drive who you call this week.
  • Act on early disengagement — declining usage, unresponsive contacts, unresolved frustration — before it becomes a renewal conversation.
  • Flag expansion signals to the Revenue team: new feature interest, usage limits, expanding use cases, new stakeholders.
  • Contribute to health scoring with what the data doesn't capture.
  • Be honest with leadership about which accounts are at risk and why.

Qualifications

• 3+ years in a customer-facing role — customer success, support, account management, implementation, or similar. SaaS experience strongly preferred.
• AI fluency, in practice.
• Genuinely technical curiosity.
• Product instinct.
• Outstanding written communication.
• Strong project management instincts.
• Queue discipline.
• Real customer empathy.
• Comfortable teaching.
• Tooling experience: help desk platforms (Zendesk, Intercom, Help Scout) and CRMs (Salesforce, HubSpot). Bonus for anything you've automated across them.
• Documentation experience — you have built or maintained customer-facing docs or a knowledge base.

How We Work

We are a small team building a product that changes quickly, and we expect people to work like it. That means using AI to remove the busywork, being close enough to the product to have opinions about it, and making decisions with data rather than waiting for permission.

You will have room to define how this role works. We would rather hire someone who improves the model than someone who follows it.