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.