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Added 7 mins ago
TG
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- Full-time
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Vice President, ETF Algo Engineer
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Own production readiness and support, including testing, deployment, observability, incident analysis, and continuous improvement of live trading systems.
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BMO

Vice President, ETF Algo Engineer

Toronto, ON, Canada
FCP, Canada

Please note the base salary for this role is $160,000 CAD. · Full-time

Apply About employer

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Job details

Pay: Please note the base salary for this role is $160,000 CAD.
Job type: Full-time
Apply by: Dec 31, 2026
Experience: 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
Posting language: English
Posted: Oct 29, 2026

Original job description

Application Deadline:

12/30/2026

Address:

100 King Street West

Job Family Group:

Capital Mrkts Sales & Service

BMO Capital Markets is a leading, full-service financial services provider. We offer corporate and investment banking, treasury management, as well as research and advisory services to clients around the world. #bmocapitalmarkets

Role Summary

We are seeking an ETF Algo Engineer to design and support low-latency electronic trading algorithms for our ETF Market Making team, using AI-assisted development to improve engineering productivity, quality, and delivery. The ideal candidate combines strong software engineering and quantitative skills with knowledge of trading protocols, market data, execution workflows, as well as development and diagnostic tools. They will use AI-enabled tools throughout the software lifecycle and build systematic trading, pricing, and risk-management solutions across multiple asset types.

Key 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.
Systemically 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.

Qualifications

5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
Strong software engineering experience in Python and/or C++, including the design, testing, and support of production systems.
Fluency with modern programming concepts and the ability to work across multiple 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.

What We Are Looking For

A builder who combines engineering discipline with strong trading instincts. The ideal candidate enjoys solving complex market problems, takes ownership from design through production, thrives in an entrepreneurial environment, and is excited to scale the algorithms and technology behind a leading ETF market-making franchise.

Please note the base salary for this role is $160,000 CAD.

Salary:

Pay Type:

Salaried

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

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More about this job

Responsibilities

Design, develop, and support low-latency electronic trading algorithms for ETF market making while utilizing AI-assisted tools to improve engineering productivity. Collaborate with traders and technology teams to build systematic pricing, risk-management, and execution solutions across multiple asset classes.

Requirements

Requires 5-7 years of experience in software engineering with proficiency in Python or C++ and a post-secondary degree in a quantitative field. Candidates must possess strong knowledge of electronic trading workflows, market structure, and experience with performance-sensitive systems.

Skills

Python
C++
Low-latency trading
Electronic trading algorithms
Market data
FIX protocol
Risk management
Linux
CI/CD
Automated testing
Performance analysis
AI-assisted development
Quantitative analysis
Order management
System resiliency

Benefits

Health insurance
Tuition reimbursement
Accident insurance
Life insurance
Retirement savings plans

Visa sponsorship

Not detected in the job text

Keywords

ETF
Algo Engineer
Capital Markets
Low-latency
Electronic Trading
Python
C++
FIX
Market Making
Risk Management
Linux
CI/CD
AI-assisted development
Equities
Futures
Options
Fixed Income
FX
Order Management
Performance Optimization
Systematic Trading
Diagnostic Tools
Observability
Quantitative Skills
Software Engineering

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