Applied AI Engineer

Who We Are
Derivative Path empowers institutions across the capital markets with innovative, AI-driven technology and expert advisory solutions. Our award-winning cloud platform supports banks, credit unions, private equity firms, hedge funds, asset managers, and insurance companies in managing interest rate, FX, and commodity risks, optimizing hedging strategies, and streamlining cross-border payments. With a client base spanning over 250 financial institutions and leading private equity firms, we deliver scalable solutions that enhance risk management and drive operational performance. Through strategic partnerships with Goldman Sachs, Wells Fargo, FNBO, Q2, and Jack Henry, we provide best-in-class capabilities to help clients achieve their financial objectives in an ever-evolving market.

With a team of seasoned professionals comprised of decades of industry experience, Derivative Path offers a flexible, hybrid work environment to its 125+ employees with the ability to work remotely in Canada. The Company is dedicated to building a diverse environment and has an unwavering commitment to creating a sense of belonging for all employees.

The Opportunity
We are looking for an Applied AI Engineer to join the AI Lab team within DerivativeEDGE. Reporting to the AI Lab lead, you will work closely with Engineering, Product, and domain experts to design, build, and ship AI-powered features in a complex, high-stakes financial environment. This is a hands-on engineering role. You will move between experimentation and production, work through ambiguous problems, and deliver AI capabilities that real clients use. Generic approaches do not get you far here. The expectation is that you learn the domain, move with urgency, and build things that hold up. The core of this role sits at the intersection of Generative AI, Agentic Workflows, and Data Engineering: building LLM-powered solutions, designing agents that can reason and act across complex workflows, and making sure the right data is available to support it all. Applied to financial derivatives, these are genuinely hard problems worth solving.

What You Will Do

• Build and ship LLM-powered features across the DerivativeEDGE platform, working directly with domain experts to translate complex financial workflows into reliable AI capabilities.
• Design and implement agentic workflows that can reason, act, and recover gracefully across multi-step processes in a production environment.
• Own the data engineering layer that feeds AI systems: pipelines, retrieval architectures, context design, and data quality.
• Move fluidly between experimentation and production. You will prototype quickly, evaluate honestly, and know when something is ready to ship.
• Contribute to the AI Lab's broader technical direction, including evaluations, tooling, MLOps practices, and the patterns the team builds on.
• Depending on where projects take you, work may also touch NLP, model fine-tuning, synthetic data, or reinforcement learning. Curiosity and a willingness to build in new areas are expected

About You

• You are someone who moves with purpose. You form a view based on what you know, test it against reality, and adjust as you learn. Ambiguity is not a blocker for you; it is just the nature of early-stage problems.
• You are hands-on by preference. Writing code, building pipelines, running experiments: that is where you do your best thinking.
• You are a quick study. Financial derivatives is a specialized domain and we do not expect you to know it coming in. What we do expect is genuine curiosity, because the depth you develop here will directly shape the quality of what you build.
• You stay constructive. This is a team working on consequential problems in a demanding environment. When things go sideways, you focus on the path forward. Collaboration and good energy matter.
• You are pragmatic about tools and languages. You reach for whatever the project calls for and stay open to better options as they emerge.

Qualifications

• Building with LLMs: prompt engineering, RAG, fine-tuning, agents, or inference pipelines
• Data engineering: designing and building pipelines that feed real workflows
• ML or data science work, especially in complex or data-constrained environments
• Working knowledge of Python and common AI/ML frameworks (PyTorch, HuggingFace, LangChain, or similar)
• MLOps or production AI experience: getting models out of notebooks and into the real world
• Cloud platform experience (Azure, AWS, or GCP)
• Experience with reinforcement learning or financial derivatives is a bonus, not a baseline.

Location

• Canada

• Competitive bonus, base salary, and equity compensation
• 23 days of PTO
• Fully remote
• RRSP contribution at 3%
• Competitive health benefits

T he expected salary for this position is $110k - $150k CAD and is eligible for a discretionary bonus and equity. We will consider your skills, experience, and location when determining your pay.
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Derivative Path is an equal opportunity employer and does not discriminate based on any of the following: race, religious creed, color, age, sex, sexual orientation, gender identity, gender expression or gender characteristic, national origin, religion, marital status, medical condition, physical or mental disability, military service or veteran status, pregnancy, childbirth and related medical conditions, or any other classification protected by federal, state, and local laws and ordinances. Derivative Path offers a comprehensive benefits package, including health, dental, vision, retirement plan, contribution, and a generous paid time off policy. As part of Derivative Path’s hiring process, interviews and evaluations may be conducted using AI-assisted technology.

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