What’s in it for you as an employee of QFG?

• Health & wellbeing resources and programs
• Paid vacation, personal, and sick days for work-life balance
• Competitive compensation and benefits packages
• Work-life balance in a hybrid environment with at least 3 days in office
• Career growth and development opportunities
• Opportunities to contribute to community causes
• Work with diverse team members in an inclusive and collaborative environment

This job posting is for an existing vacancy

We’re looking for our next Principal AI Engineer. Could It Be You?

The Principal AI Engineer is a comprehensive, hybrid role requiring deep full-stack engineering discipline. You will be responsible for embedding foundational AI models into our high-frequency trading platforms, fine-tuning and optimizing models for low-latency financial contexts, and architecting autonomous, self-correcting agent systems that can handle complex multi-step investing workflows.

Need more details? Keep reading…

In this role, responsibilities include but are not limited to:

AI Systems Engineering:

• Build and maintain the underlying infrastructure required to deploy AI within a high-performance brokerage environment.
• Design scalable REST/gRPC APIs, manage vector embeddings of market data, and integrate LLM orchestration layers cleanly with Questrade’s existing C#/.NET microservices, Angular/Next.js frontends, and GCP cloud infrastructure.
• Consistently evaluate emerging AI trends and frameworks to build new and better ways for the platform to remain a market leader.

Model Optimization & Productionization:

• Adapt open-source and frontier models to the nuances of Canadian financial markets.
• You will fine-tune models (using LoRA/QLoRA) on proprietary market research, client portfolios, and compliance data. Optimize models for maximum throughput and minimum latency to ensure real-time response times in active trading dashboards.

Autonomous Brokerage Workflows:

• Design and implement stateful multi-agent systems using frameworks like LangGraph or custom runtime loops.
• Build autonomous "digital investment assistants" capable of multi-step execution—such as checking account balances, querying market data streams, analyzing asset allocations against a user’s risk profile, drafting rebalancing orders, and routing them safely to human validation queues.

Guardrails, Compliance & Auditing:

• In a heavily regulated brokerage space, safety is non-negotiable. Implement strict deterministic guardrails, prompt injection defenses, and real-time automated audit frameworks using Kafka data streams.
• Ensure all AI actions are auditable, verifiable, and adhere to strict regulators and privacy compliance standards.

Cross-Functional Collaboration:

• Partner closely with software and data engineering squads, product managers, and cybersecurity to embed intelligence capabilities smoothly into brokerage products.

• Communicate complex technological concepts and algorithmic logic clearly to non- technical business partners.

So are YOU our next Principal AI Engineer? You are if you…

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a closely related quantitative field.
• Experience: 7+ years of professional software engineering experience, with 2+ years of dedicated experience shipping production-grade Generative AI, RAG, or Agentic features to end-users.
• Strong proficiency in Python (FastAPI, PyTest) paired with experience in enterprise ecosystems like C#/.NET Core, Node.js/TypeScript, or C++.
• Hands-on experience within a cloud-native architecture (preferably GCP) using Docker, Kubernetes, and infrastructure-as-code (Terraform). Strong database skills across Google Cloud SQL, BigQuery, and NoSQL solutions (MongoDB, Redis).
• Proven experience building complex RAG pipelines and orchestrating multi-agent systems utilizing LangGraph, CrewAI, Semantic Kernel, or Model Context Protocol (MCP). Proficient with vector databases
• Deep understanding of software design patterns (Domain-Driven Design), event-driven architectures (Kafka, Google Pub/Sub), and handling real-time, low-latency data streams.
• Demonstrated ability to approach intricate business barriers with an analytical, innovative mindset

Compensation Information:

• Base salary range: $150,000 - $190,000
• The final compensation package will be commensurate with the successful candidate's experience, skills, and geographic location (Canada). It includes a comprehensive benefits plan and a competitive incentive (bonus) program for Full-Time Permanent roles.