Senior Manager, Learner & Client Support
Multiverse
| Company | Multiverse |
| Category | HR & Recruiting |
| Location | London |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 2 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
Multiverse is the upskilling platform for AI and Tech adoption.
We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.
Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
In April 2026, we announced $70 million in strategic funding, led by Schroders Capital, with participation from StepStone Group, Lightspeed Venture Partners and General Catalyst. At an increased valuation of $2.1bn, the round makes us Europe’s first EdTech double unicorn.
But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.
Join Multiverse and power our mission to equip the workforce to win in the AI era.
The Opportunity
Multiverse is building the AI-first workforce transformation platform that connects learning to career outcomes at scale. As we scale toward $1bn+ in bookings, we are investing in support as a strategic function: a new operating model, modern infrastructure, and a function that actively strengthens learner retention and customer trust.
This is a rare clean-sheet opportunity. In your first six months, you will design the support operating model from first principles and build the platform that runs it. Beyond that, you own the strategy, the operating model, and the long-term performance of support for a genuinely multi-sided audience: learners, the coaches who guide them, and the employers who fund them.
This is a build role, not a queue-management role. A Support Manager runs the day-to-day team and SLA delivery and reports to you. You set the direction, design the system, and hold the function to a standard the business can trust.
What You Will Own
The Build (First 6 Months)
- Own the support infrastructure programme end to end: assess the current setup, design the target state, coordinate the build, manage cutover, and stabilise. A defined programme with clear milestone gates and acceptance criteria.
- Design the support experience from first principles for each requester type (learner, coach, employer, internal Multiverse seller): what happens at every touchpoint from first contact to resolution, including communication, escalation, waiting states, and AI-to-human handoffs. The journey design drives system configuration, not the other way around.
- Translate that design into Intercom configuration: taxonomy, workflow architecture, SLA definitions, routing, snooze protocols, ticket transparency, and native reporting. Every system decision traces back to a journey decision.
- Act as single-threaded owner of the programme. You PM Intercom Professional Services and develop the internal technical specialist who will own the configuration long term.
Support Strategy & Operating Model (Ongoing)
- Own the operating model and its evolution as volume patterns shift, new products launch, and AI capability expands. Set the roadmap two quarters ahead and hold delivery to the current one.
- Design the metric framework across leading, process, and output layers, with first contact resolution and re-contact rate as honest measures of quality rather than activity.
- Build and present the business case for support investment as revenue protection
AI Resolution & Knowledge
- Define the AI resolution roadmap: which journeys move to AI, in what order, at what quality threshold, with humans kept in the loop on policy-sensitive cases (safeguarding, funding eligibility, qualification decisions).
- Set the knowledge system and standards that power both agents and AI, and coach the Knowledge Manager who owns it day to day. A strong knowledge foundation is what makes scaled AI resolution possible.
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