Applied AI Engineer

Derivative Path • Toronto, ON

8d • CA$110,000 - CA$150,000 • Remote

About The Position

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.

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.

Requirements

• 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)

Nice To Haves

• Experience with reinforcement learning or financial derivatives is a bonus, not a baseline.

Responsibilities

• 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

Benefits

• Competitive bonus, base salary, and equity compensation
• 23 days of PTO
• Fully remote
• RRSP contribution at 3%
• Competitive health benefits
• health, dental, vision, retirement plan, contribution, and a generous paid time off policy.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed