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Development Team for Internal Tools | Payments Experience & AI-Assisted Development

Budget
$25.0 - $47.0
Contract
HOURLY / FULL_TIME
Client
United Kingdom
Live feed
Upwork

web-programming, api-integration, product-management, python

Preferred qualifications

  • Experience: Expert
We’re a technology company working in iGaming. While our in-house engineers focus on our main portal, we’re building a pool of external development teams to deliver smaller internal tools. The tools will vary. Hands-on experience with payment processing is required, and iGaming experience is a plus. For each tool, we’ll share a brief and ask for your recommended approach, quote, and timeline. We’ll award projects individually. Your team will own delivery from brief to production, working directly with our project manager, product owner, and relevant stakeholders. What we’re looking for Engineers who move work forward. If you see a simpler way to achieve the business goal, propose it. If a decision is blocking progress, bring the right person a clear question and a recommendation. Agree on what stakeholders can try first, show it early, and flag anything that puts delivery at risk. Proven use of AI to speed up delivery. We want a team that already uses Claude Code, Cursor, Codex, or similar tools and can demonstrate where that shortened a real project. We value engineers who know when to move quickly and when a payment rule or failure scenario needs closer review. Your team should understand the code it ships and be able to test, maintain, and fix it in production. Practical payments knowledge. The engineers doing the work should have built software for payment operations such as transaction processing, payouts, routing, settlement, or reconciliation. We value people who can recognize an important gap in a brief because they’ve dealt with that workflow before. In your proposal, please answer three questions Describe one payments tool the engineers assigned to us personally shipped. Who used it, and what did your team need to understand about the payment flow to get it right? Give one example where AI helped your team deliver faster. What part of the work did it accelerate, roughly how much time did it save, and how did your engineers verify the result? Tell us about a project where your team spotted an unnecessary step or a missing decision and took the initiative to resolve it. What did you change, who did you involve, and how did it affect delivery? Short, specific examples are ideal. Anonymized projects are welcome.
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