Senior Product Manager - Algorithmic Trading

Overview

• Kraken is building the execution infrastructure that will power the next generation of professional and institutional crypto trading and, increasingly, the AI agents that trade on their behalf.
• This role sits at the heart of that mission: owning the Algorithmic Execution & Strategy Engine, Kraken s platform for complex order types, smart execution algorithms, and programmable strategy construction.
• We are looking for a product manager who has lived and breathed electronic trading in a Tier 1 bank or algorithmic trading firm someone who has shipped execution algos, spoken FIX with quant developers, and understands why basis points matter.
• Your mission is to port the best of TradFi execution into crypto and build the platform that both humans and AI agents will rely on to execute with precision.
• The opportunity
• 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.