Vice President, ETF Algo Engineer

BMO•New York, NY

20h

About The Position

BMO Capital Markets is seeking an ETF Algo Engineer for its ETF Market Making team. The role designs and supports low-latency electronic trading algorithms, using AI-assisted development to improve engineering productivity, quality, and delivery. The successful candidate combines software engineering and quantitative skills with knowledge of trading protocols, market data, execution workflows, and development and diagnostic tools. The position builds systematic trading, pricing, and risk-management solutions across ETFs and related asset types. It also owns production readiness and support, including testing, deployment, observability, incident analysis, and continuous improvement of live trading systems. The role partners with traders and engineering, technology, operations, and control functions to turn desk priorities into reliable, compliant production solutions.

Requirements

5–7 years of relevant experience and a post-secondary degree in a related field, or an equivalent combination of education and experience.
Strong software engineering experience in Python and/or C++, including designing, testing, and supporting production systems.
Fluency with modern programming concepts and ability to work across commonly used languages, scripting environments, APIs, and data formats as the platform requires.
Experience developing electronic trading algorithms, low-latency systems, real-time applications, or other performance-sensitive software.
Knowledge of electronic trading workflows, market data, order lifecycles, and protocols such as FIX or venue-native interfaces.
Understanding of ETFs, market structure, pricing, execution, hedging, and risk management across one or more related asset types.
Experience with Linux, source control, automated testing, CI/CD, observability, performance analysis, and production diagnostic tooling.
Ability to analyze large market and trading datasets and translate findings into reliable engineering solutions.
Effective use of AI-assisted development tools, with sound judgment around validation, security, and software quality.
Strong problem-solving, communication, and collaboration skills in a fast-paced trading environment.
Post-secondary degree in Engineering, Computer Science, Mathematics, Statistics, Physics, Finance, or a related field, or an equivalent combination of education and experience.

Responsibilities

Design, develop, test, and support low-latency algorithms for ETF pricing, quoting, execution, hedging, and inventory management.
Build systematic trading, pricing, and risk-management tools across ETFs and related asset types, including equities, futures, options, fixed income, and FX.
Integrate exchange, broker, market-data, and RFQ connectivity.
Develop reusable trading services and desk tools for market data, fair value, order management, risk controls, automation, and workflow integration.
Measure and optimize latency, throughput, fill quality, markouts, quote performance, and system resiliency across the trading stack.
Create simulation, replay, monitoring, and diagnostic capabilities using application, market, and packet-level data.
Own production readiness and support, including testing, deployment, observability, incident analysis, and continuous improvement of live trading systems.
Apply AI-assisted development tools to accelerate implementation, testing, documentation, and code quality while adhering to engineering and security standards.
Enable new ETFs, venues, trading workflows, and asset structures through scalable configuration and platform enhancements.
Partner with traders, engineering, technology, operations, and control functions to translate desk priorities into reliable, compliant production solutions.