AI Trading Engine Implementation for Cryptocurrency Transactions

Kevin Toles

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Program Manager

Confluence

Jira

Problem: Coinme faced substantial financial exposure due to cryptocurrency price volatility and inefficiencies in manual transaction processing.
Scope: Within a tight 6-8 week timeframe, the project involved implementing an AI trading engine to batch transactions, reduce fees, enhance privacy, and ensure faster settlements. This required orchestrating collaboration across engineering, product, and financial teams to define critical requirements, managing an architectural review process, and balancing resource planning with ongoing commitments. The implementation aimed to minimize financial risks and optimize resource utilization by automating transactions.
Results: The AI engine successfully mitigated financial exposure from a $193B to $1.67T trading surge, significantly optimizing transaction processing and reducing manual intervention. The project demonstrated effective leadership under tight deadlines, aligning with Coinme's strategic goals and improving overall operational efficiency.
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Posted Aug 7, 2024

Implemented AI engine, batching transactions to reduce fees, enhance privacy, and optimize settlements, mitigating exposure during a $193B-$1.67T trading surge.

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Coinme

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Program Manager

Confluence

Jira

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