Member self-service
Building in-app experiences that let members resolve their own issues quickly and confidently - without needing to speak to a human.
Think: dispute flows, fraud reporting, account recovery, downgrade queries.
The goal is members who sort it themselves, not one who opens a support ticket.
Internal tooling for Ops, Fraud & Support
The tools our internal teams use directly determine how fast and well they can help members.
You'll own the agent-facing experience - building and improving the tooling that helps our Support, Fraud, and Operations teams investigate cases, take action, and close tickets with less effort.
Less clicking, less switching, more resolution.
Deflection and contact rate reduction
Working across the product to identify the root causes of member contact - the bugs, confusing flows, and missing self-serve options that generate avoidable inbound.
You'll be the PM who asks "why did this member need to contact us at all?" and then fixes it upstream.
AI and automation
Embedding AI across both directions: helping members get answers faster through intelligent chat and smart search, and helping agents work more effectively through summarisation, auto-classification, and suggested next actions.
You don't need to be an AI engineer - you need to know how to ship AI-powered products that actually work in production.

Requirements

You've shipped products that reduced operational load.
You understand that the best support product is often the one that means members don't need support at all.
You've built self-serve flows, deflection tools, or internal tooling at a company where contact rate was a real metric.
You're comfortable in the messy middle.
This role sits across Fraud, Operations, and Support – three teams with different incentives, different risk tolerances, and different definitions of a good outcome.
You'll need to build trust with all of them and translate between them.
You think in systems.
You can look at a spike in contact volume and trace it back to a product decision made three months ago.
You design feedback loops, not just features.
You're data-driven, but not data-dependent.
You know how to use SQL to pull your own answers, talk fluently with data, and make decisions when the data is ambiguous.
You understand AI/ML in practice.
You've worked with LLMs, retrieval systems, or automation tooling in production - not just in a prototype.
You know the difference between what a model can reliably do and what it can't.
Attention to detail.
You’re able to zoom in and obsess about small details that benefit customers.
You care about member experience even when it's operationally convenient not to.
You work like it’s 2025.
AI tools are a natural extension of how you work - brainstorming with ChatGPT, spinning up concepts in Figma AI, generating SQL, summarising research.

Benefits

35 holidays (27 days annual leave + 8 days public leave)
2x team-building offsites per year (1 in the UK, 1 abroad)
Private healthcare with Vitality, including mental health, dental & vision cover
Up to 12 weeks enhanced parental leave after being with Yonder for 1 year
Learning & training allowance (£750/year) that you can use on books, courses, etc
Regular team breakfasts and lunch
Regular team events like Mini-golf, Escape Room, Cocktail making
Cycle-to-work scheme
Fresh pour-over coffee made by our very own CEO, Tim

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLAIMLautomation toolingself-serve flowsdeflection toolsinternal toolingdata-driven decision makingproduct managementfeedback loop design

Soft Skills

attention to detailtrust buildingsystem thinkingcommunicationproblem solvingdata fluencyadaptabilitycollaborationcustomer experience focuscross-team translation