As AI Specialist, you'll build Flatpay's AI-powered KYC and onboarding capability from the ground up. You’ll use best-in-class tools, be supported by the AI & Toolings team, and no developer skills are required. That means identifying where AI and OCR tooling can eliminate manual work, evaluating and selecting the right solutions, and doing the hands-on operational work (and testing) to get them running accurately across all our markets.
Today, this process is largely manual. You'll change that. You'll own the journey from mapping what we have, to designing what we need, to implementing and continuously improving it - with a singular goal: getting merchants live faster, with less friction for everyone involved.
In practice, your work will include:
- Map and audit the current KYC and onboarding process end-to-end across markets - documenting manual steps, bottlenecks, and the document and data requirements that vary by country – together with the local teams
- Identify where AI and OCR tooling can have the biggest impact - document scanning, data extraction, and the likes
- Evaluate and onboard best-in-class AI tools, working closely with tech and compliance stakeholders to assess fit, accuracy, and regulatory compatibility
- Do the operational groundwork that makes AI perform - structuring document requirements, defining acceptance rules, mapping edge cases, and building the knowledge base that the tooling depends on
- Validate and fine-tune - testing input/output quality across document types, languages, and markets, and iterating until performance meets the bar – all while executing
- Work with local teams to adapt tooling and rules to each market's document standards, regulatory requirements, and language nuances
- Support Ops teams, field sales, and local leadership with clear playbooks and guidance so they can work confidently within new processes and resolve onboarding blockers without unnecessary back-and-forth
- Track and report on impact - time-to-onboard, manual review rates, AI accuracy, and rejection reasons - using data to demonstrate progress and guide the next iteration
- Execute ruthlessly – this role is expected to hit the ground running, iterate and test as fast as possible, and have this live across markets within a few months