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About the Role

The Quant Systems Engineer plays a critical role in enabling and scaling quantitative solutions used by investment teams. This role partners directly with Front Office investment teams to co-develop solutions while contributing to the robustness, standardization, and long-term supportability of the underlying analytics platform. As a Quant Systems Engineer, you will help transform quantitative investment workflows into robust, reusable, and production-ready solutions. You will work closely with portfolio managers, quants, researchers, traders, and investment teams to understand analytical requirements, engineer scalable implementations, and ensure solutions can evolve beyond a single use case or team. You will also help integrate modern AI capabilities and reliable data pipelines into quantitative workflows, ensuring that new capabilities are practical, observable, and aligned with investment use cases. This is a hands-on technical role for someone who enjoys building high-quality software, working close to investment decision-making, and solving engineering challenges in a quantitative environment. While the role requires credible quantitative fluency, it is not intended to be a Front Office quant research role.

Responsibilities

Co-design and co-develop quantitative solutions supporting investment workflows.
Translate research, investment, and analytical workflows into production-ready implementations.
Act as a technical counterpart who understands both quantitative intent and platform constraints.
Support the full lifecycle of quantitative solutions, from design and deployment through ongoing evolution.
Bridge the gap between investment requirements and engineering implementation.
Help teams standardize and operationalize analytical workflows.
Collaborate with data engineering partners to ensure quantitative solutions are supported by reliable, validated, and well-orchestrated data pipelines.
Identify opportunities to incorporate AI-assisted capabilities, automation, and intelligent workflow support where they can improve speed, quality, or decision support.
Define, implement, and maintain reusable engineering capabilities, solution patterns, and development standards that enable quantitative solutions to scale across investment teams.
Identify opportunities to generalize solutions across teams and investment functions.
Contribute reusable Python packages, libraries, frameworks, and engineering practices that improve consistency across teams and environments.
Ensure deployed solutions are maintainable, scalable, and supportable.
Contribute to documentation, standards, and best practices for quantitative application development.
Define reusable patterns for integrating modern AI capabilities into analytical and quantitative workflows, including responsible experimentation, validation, and operationalization.
Improve the robustness of analytics and quantitative computing environments across production and non-production environments.
Contribute to migrations, upgrades, and platform standardization initiatives.
Build tooling, automations, and platform capabilities that directly support quantitative workflows.
Participate in incident triage, root-cause analysis, and continuous improvement efforts.
Help improve deployment, monitoring, troubleshooting, and operational support processes.
Contribute to pipeline reliability through orchestration, observability, data quality checks, and clear operational runbooks.
Design, build, and support data pipelines that connect source data, analytical transformations, model logic, and downstream reporting or application layers.

Requirements

Strong Python software engineering skills, including production-grade development practices.
Experience designing maintainable, modular, and reusable software solutions.
Experience working in data-intensive, analytics-heavy, or quantitative environments.
Familiarity with cloud-native development environments and shared tooling ecosystems.
Working knowledge of Git-based development workflows, code reviews, and CI/CD concepts.
Experience building internal tools, libraries, automation capabilities, or shared engineering components.
Strong debugging and problem-solving skills across both research and production contexts.
Ability to diagnose issues spanning application logic, orchestration, data dependencies, and runtime environments.
Familiarity with modern AI capabilities, AI-assisted development practices, or applied AI/ML solutions in an enterprise setting.
Experience designing or supporting ETL/ELT, orchestration, data validation, and data quality patterns for analytical or quantitative workflows.
Solid understanding of quantitative concepts such as Time-series analysis, Financial instruments and risk concepts, Modeling, backtesting, and performance evaluation.
Ability to read and understand quantitative logic.
Ability to collaborate effectively with quants, researchers, and investment professionals.
Ability to translate quantitative requirements into scalable technical solutions.
Ability to balance engineering rigor with practical investment needs.
Strong collaboration skills across investment, quant, data engineering, and platform teams.
High ownership and ability to operate autonomously.
Ability to manage ambiguity and drive technical initiatives to completion.
Product-oriented mindset focused on maintainability, supportability, and reuse.
Strong communication skills with both technical and non-technical audiences.
Ability to balance short-term delivery requirements with long-term platform sustainability.
Pragmatic engineering judgment and continuous improvement mindset.
Experience working directly with Front Office or investment teams.
Prior exposure to quantitative finance, trading, portfolio management, or risk environments.
Experience supporting internal platforms, developer platforms, or shared services.
Familiarity with modern orchestration, containerization, and automation frameworks.
Exposure to cloud-native architectures and scalable application development.
Experience contributing to platform engineering, developer enablement, or internal tooling initiatives.
Experience with data pipeline orchestration, data quality automation, or analytical data product development.
Experience integrating AI capabilities into production or near-production workflows with appropriate validation, controls, and monitoring.
Intermediate proficiency in French, as the candidate will be required to communicate daily with French-speaking clients and partners across Canada via email and phone calls.

Skills

Python
Software Engineering
Data-intensive environments
Analytics-heavy environments
Quantitative environments
Cloud-native development
Git
CI/CD
Internal tools development
Library development
Automation capabilities
Shared engineering components
Debugging
Problem-solving
AI capabilities
AI/ML solutions
ETL/ELT
Orchestration
Data validation
Data quality
Time-series analysis
Financial instruments
Risk concepts
Modeling
Backtesting
Performance evaluation
Quantitative fluency
Collaboration
Communication
Product-oriented mindset
Engineering rigor
French

Location

Quebec / 1080, Grande Allee West
Montreal / 1981 McGill College Avenue
Toronto / 26 Wellington Street East

Work Type

Hybrid

Experience Level

5+ years of relevant experience for intermediate candidates
8+ years for senior candidates

Education Level

Undergraduate or master’s degree in Computer Science, Engineering, Mathematics, Finance, Financial Engineering, or a related field preferred.
CFA, CQF, FRM, or other quantitative or financial designation is considered an asset.

Salary/Compensations

70,000$ and 110,000$ CAD per year

Benefits

Flexible group insurance
Competitive pension plan
Stock purchase plan
Vacation and wellness/personal development days
Telemedicine
Employee and family assistance program
Ergonomic furniture program
Performance bonus
Discounts on iA products

About the Company

iA Financial Group is the strength of a company with a human side, with its over 8,000 employees.
Together, we have earned the trust of our more than four million clients and 25,000 advisors who have chosen us for their insurance, savings, and wealth management.
With over $200 billion in assets and half a billion invested in technological innovation, we’re a key player in the financial services industry in Canada and the United States.
The secret to our success? Investing in you, one person at a time.
For over 125 years, we have believed that it’s by supporting our employees and surrounding ourselves with the most reputable leaders in the industry, we will continue to innovate.
At iA, we’re invested in you.

Equal Opportunity

At iA Financial Group, we support and celebrate diversity.
We strive to provide a workplace that is recognized as inclusive for all, regardless of ethnic origin, nationality, language, religious beliefs, gender, sexual orientation, age, marital status, family situation, or physical or mental disability.
Please note that if you need help or assistance to make the recruitment process more accessible for you, please Contact us here. Someone from our team will be happy to assist you with your needs.