Engagement Associate
- Market p25–p75
- £33k–£53k
- Opened · 30d
- +0
- Closed · 30d
- −0
- Opened · 7d
- +3,1469% of open
- All other
- 625,257open
Metaview is an AI company focused on recruiting. We build AI agents that help world-class companies hire with radically more speed and precision. We automate the toil, and augment the human for companies like Brex, Affirm, Deel, ElevenLabs, and Airtable.
Founded by Siadhal and Shahriar after their experiences scaling Uber and Palantir, we’ve raised $110m from top-tier investors including Google Ventures and Insight Partners.
It’s still day 0: Now is the time to re-engineer how work gets done with AI at the core, and our toughest challenges still lie ahead. We’re looking for people seeking the hardest, most fulfilling work of their lives.
How we work
Four principles guide us:
Velocity. Optimise for rate of learning. Take action, get feedback, get better.
Hospitality. Sweat the experience. Delight customers, candidates and colleagues, even when it’s inconvenient.
Transparency. Public unless private. Share context openly within the company so people and agents can take initiative.
End-to-end. Deliver outcomes, not tasks. Step beyond your job description and see the work through.
The role
Part solutions, part AI builder, commercially owned, on a book of smaller, faster-moving customers. You'll own those accounts end to end, with a high degree of autonomy. You run the onboarding and shape the implementation around what the customer is actually trying to fix in how they hire. Then you stay with them: running enablement as teams and our agents change, partnering deeply with our customers to notice when something is off before anyone raises it or where one of our agents could help solve an emerging problem.
Fewer stakeholders and shorter cycles than our largest customers, which means decisions get made in the room and you find out quickly whether your call was the right one.
Customers get their value from an instance shaped around them: custom note templates, the reports and analytics that answer the questions their leadership is asking, workflows that fit how they actually hire. You’ll build that with them. You’ll also own a few larger accounts, where the horizon is longer, the organisation is more complex, and you’re moving a wider set of stakeholders toward the same outcome.
It suits someone who gets close to a product. The best people in this seat know Metaview better than anyone outside engineering, and can tell when a customer's problem is a configuration change rather than a feature request.
Key ownership areas:
Own retention and growth on your book. GRR and NRR, with the renewals and expansion conversations that produce them.
Own your customers' outcomes end to end. Onboard them well, get them to value quickly, and stay close through the full customer lifecycle - because that's what the number rests on.
Be a partner, not a ticket queue. Run the sessions, make recommendations, and have a view on how they should be hiring and utilizing our agents.
Go deep on the product. Know what it does, where it bends, and what's coming.
Build with AI. Automations, agents, internal tools - we'd rather you engineered the admin away than powered through it.
Do your own analysis. We have no separate data team. You'll read usage data yourself, spot risk and expansion signals early, and know when to escalate.
Close the loop with Product. You'll see the same friction repeatedly before anyone else does. Make it impossible to ignore.
What you bring
Anywhere from 1-4 years post-academics, with some experience in one of the following: consulting, customer success, or advisory; an ops, growth, GTM, analyst, chief-of-staff, or product-adjacent role at a software or AI company; or a junior role at a strong company with clear upward trajectory.
An appetite for the commercial side. You don't need to have owned a retention number yet, but you should want to, and be able to show you've been close to revenue, targets, or customers whose spend depended on your work.
Genuine, hands-on AI engagement. Shipped projects are the strongest signal, but hackathons, coursework, prompt-engineering work, published writing, or time at an AI-native company all count. What matters is that it's real.