Head of Trading Infra

Role Overview

We are looking for a Head of Trading Infra to build and lead a centralized team responsible for the firm's exchange-facing trading connectivity across global markets.The scope covers exchange raw market data ingestion (Feed Handlers) and order entry (Order Entry / Gateway) systems, and delivers raw historical market data that remains consistent with the live trading path. The mandate is to build a normalized, reusable connectivity framework across markets and asset classes. The framework should provide common architecture, protocol abstractions, normalized data formats, monitoring, and quality controls, while still allowing market- and exchange-specific adaptations. The goal is to provide low-latency, reliable, consistent, and scalable infrastructure for the firm's quantitative trading business.

Key Responsibilities

• Own the architecture and technical direction of the firm's global exchange connectivity infrastructure, covering raw exchange market data ingestion, order entry gateways, and raw historical market data.
• Build a cross-market framework that enables efficient onboarding of new markets, exchanges, and asset classes through a unified architecture, protocol abstractions, normalized data formats, and quality standards.
• Drive continuous improvement of the software trading path across latency, reliability, accuracy, monitoring, failure recovery, and capacity planning.
• Establish consistency standards and validation mechanisms across live market data, order entry, and raw historical market data, ensuring consistency across research, backtesting, simulation, and production trading.
• Collaborate with trading, research, risk, operations, Colo/Infra teams, as well as external exchanges, raw market data vendors, and connectivity service providers, translating business requirements into clear technical plans, connectivity solutions, and deliverable projects.
• Build and lead the team, including hiring, coaching, organizational design, project prioritization, delivery cadence, and engineering standards; and continuously improve the team's overall capabilities in low-latency trading systems, market protocols, data quality, and global market connectivity.

Requirements

Must-have

• Bachelor's degree or above in Computer Science, Financial Engineering, Mathematics, or a related quantitative or technical discipline.
• Experience designing or leading normalized Feed Handler and Order Entry Gateway frameworks across multiple markets, including protocol abstraction, data standardization, market-specific adaptation, replay validation, and production deployment. Equivalent experience owning end-to-end productionization of Feed Handler / Gateway systems for major markets is also acceptable.
• Strong proficiency in C++, with solid experience in low-latency system development and deep familiarity with memory management, concurrency models, network I/O, protocol parsing, CPU/cache behavior, latency measurement, and performance tuning on performance-critical paths.
• Deep understanding of low-latency path design and diagnostic systems for trading connectivity, with the ability to guide the team in building tools and capabilities for packet-level / pcap analysis, data replay, protocol-level issue diagnosis, end-to-end latency analysis, failure reproduction, and quality validation.
• 8+ years of relevant experience at a quantitative trading fund, exchange, market maker, or similar institution, including at least 3 years of people management or technical leadership experience.
• Strong understanding of how trading infrastructure impacts strategy performance, trading stability, and business outcomes; ability to effectively align requirements and priorities across trading, research, risk, and engineering teams, and lead the team to deliver efficiently in a fast-paced environment.

Nice-to-have

• Deep experience in specific markets, with priority in the following order: US equities > APAC equities > CME and other futures markets > others.
• Experience working with large-scale raw exchange market data, including raw historical data parsing, backfilling, completeness validation, replay, quality governance, and online/offline consistency validation.
• Familiarity with Python and common data analysis tools for market data validation, issue investigation, research support, and production diagnostics.
• Familiarity with major exchanges, raw market data vendors, and connectivity service providers, including their product coverage, data quality, support capabilities, and cost structures; experience evaluating vendors and making technical selection decisions.