AI Operations Specialist

Confirmed live in the last 24 hours

Capital on Tap

London

On-site

Posted April 23, 2026

Job Description

We’re Capital on Tap
Capital on Tap started because small businesses were underserved. Big banks were slow, their products weren't fit for purpose, and small business owners often couldn't access what they needed. We set out to fix that.

Today we're a financial platform - not just a credit card company. We offer a best-in-class business credit card, SME-focused spend management platform, a savings product that hit £1 billion in funds within its first year, and a growing suite of tools and financial products that make running a small business easier.

1,000+ employees, £20bn in annual card spend, 200,000+ customers, 17,000+ Trustpilot reviews averaging 4.7 stars, and we're profitable. We’ve done a pretty good job so far, but we’re just getting started!

London (Moorgate) | 3 Days in Office

The Role

Most companies talk about AI. We’re building the infrastructure to make it stick. This role exists to close the gap between AI’s potential and what our teams actually use every day. You’ll identify where AI can have real impact across the business, build and deploy working solutions fast, and make sure they get used, not just launched.

This isn’t a research or strategy role. You’ll be shipping automations, coaching teams, measuring adoption, and iterating until it works. If you’d rather be doing than advising, this is for you.

What You’ll Be Doing

Design and build multi-step agentic workflows that connect AI models with internal systems - case management tools, APIs, and data platforms - to automate high-volume, rule-heavy Ops processes like complaints triage, dispute handling, and case routing.
Work closely with the Operations team to map processes end-to-end, identify high-value automation opportunities, and ship working solutions directly into their day-to-day tooling - not prototypes handed off to engineers.
Own the full workflow lifecycle: from scoping and building to debugging production issues, iterating on live automations, and handing over to teams with clear documentation and training.
Measure adoption and impact of every tool you deploy, and iterate until active usage is the norm, not the exception.
Coach internal AI champions and embed AI-first practices into how teams actually work day to day.
Maintain CoT's AI playbook, documenting what works and scaling it across the business.
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