• Own and drive the roadmap for Kraken’s Algorithmic Execution & Strategy Engine, defining the multi-year vision and aligning it with Kraken’s institutional and pro-trading growth strategy. • Design and deliver new execution algorithms — TWAP, VWAP, Implementation Shortfall, Participation, scaled orders, and conditional order flows — drawing on deep knowledge of TradFi execution best practice. • Build out the strategy construction interface — a programmable layer that allows professional traders and institutions to compose, test, and deploy execution strategies without writing code. • Own the API and FIX protocol specification for programmatic access to the algo engine, working closely with engineering and client solutions to ensure low-latency, high-reliability access for institutional clients. • Define transaction cost analysis (TCA) and execution quality frameworks; work with the data science team to instrument, measure, and continuously improve execution performance. • Establish the agentic integration framework: design the interfaces and capability set that allow AI trading agents to interact safely and effectively with Kraken’s execution infrastructure. • Partner with Quant Research and Engineering to evaluate and integrate ML/AI-driven enhancements to the execution stack, including adaptive routing and predictive scheduling. • Engage directly with institutional clients, prime brokerage relationships, and professional traders to surface execution needs and translate them into product requirements.