Job Description North American Centre, 5700 Yonge St #210B, North York, ON M2M 4G3, Canada Questrade Financial Group (QFG) through its companies provides securities and investment services, mortgages, real estate services, and more. We are hiring a Principal AI Engineer – a hands‑on technical leader and force multiplier in AI Engineering & Enablement. Benefits Health & wellbeing resources and programs. Paid vacation, personal, and sick days. Competitive compensation and benefits packages. Work‑life balance in a hybrid environment with at least 3 days in office. Career growth and development opportunities. Community contribution opportunities to support various causes. Inclusive environment working with diverse team members in a collaborative setting. Responsibilities Define and drive technical direction for complex initiatives within the AI Engineering & Enablement charter and squad‑aligned priorities. Lead solutioning for ambiguous problems by producing crisp technical artifacts (RFCs, decision records, runbooks, evaluation summaries, and onboarding guides) that enable teams to move faster. Lead spikes, reference implementations, and critical‑path engineering work; perform code reviews and pairing to uplift engineering quality and consistency. Establish and evolve safe, scalable patterns for AI‑assisted development and automation—including coding assistants, agent workflows, tool‑use patterns, retrieval and RAG patterns, and evaluation/traceability approaches that improve engineering velocity without compromising controls. Contribute to test strategy, quality gates in CI/CD, and AI‑assisted testing approaches that fit regulated engineering standards. Partner with security, enterprise architecture, and cloud platform teams so designs reflect identity, access, spend guardrails, auditability, operational ownership, and standards for AI APIs and AI CI/CD. Connect product and platform teams so promising ideas mature into deployed, consumed capabilities. Improve instrumentation and feedback loops (dashboards, limits, alerts, lightweight metrics) so adoption and risk are visible to leadership. Mentor engineers through complex technical challenges; facilitate productive conversations across engineering, risk, and leadership during planning, incident learnings, and architecture reviews. Represent engineering positions in working groups; articulate trade‑offs, sequencing, and costs with clarity; and document decisions for durable alignment. Support technical assessments, PoCs, and review of partner or external engineering deliverables against defined standards and acceptance criteria. Deliver measurable impact aligned to squad roadmap through shipped improvements, reusable templates, and reference implementations within 6–12 months. Qualifications BS or Master’s degree in Computer Science, Information Systems, Systems Engineering, or a related field (or equivalent combination of education and experience). 10 years of professional software or systems engineering experience with a proven track record shipping features in ambiguous, cross‑team environments typical of senior IC scope. Familiarity with metrics (Datadog, OpenTelemetry) and FinOps principles in a production environment. Demonstrated experience building or operating LLM‑, agent‑, or ML‑backed capabilities in production, or an exceptional combination of strong software delivery plus deep applied AI engineering experience. Hands‑on mastery in at least one modern engineering stack used for services or automation (Python, TypeScript/Node, or .NET). Strong experience with CI/CD, software quality practices, and operating services with attention to reliability, performance, and observability. Familiarity with LLM application patterns (including RAG and retrieval design), agent orchestration concepts, workflow automation platforms, and evaluation/observability approaches for non‑deterministic systems. Practical grounding in APIs, microservices, and data governance considerations for AI model serving and data flows. Experience with enterprise identity, SaaS administration models, and common engineering collaboration tooling (GitLab, Jira, Confluence). Experience with major cloud providers (GCP) and cloud‑native practices. Excellent written and verbal communication skills; ability to translate technical concepts for engineering, risk, and leadership audiences. Proven success influencing outcomes within technical priorities agreed with engineering leadership without direct people‑management authority. Experience in regulated or high‑stakes environments (financial services preferred) and familiarity with compliance and security constraints for AI infrastructure. Hands‑on experience implementing AI security controls including prompt injection mitigation, output filtering, and PII detection. Familiarity with AI governance frameworks and responsible AI engineering practices (model audit logging and fairness monitoring). Demonstrated ability to influence technical direction at organizational level through architecture reviews and cross‑functional stakeholder engagement. Contributions to technical standards or communities of practice, human‑in‑the‑loop automation patterns, vendor PoC evaluations. Contributions to open‑source AI/platform engineering projects, technical publications, or conference presentations at recognized forums. This role requires three days of in‑office presence per week for Greater Toronto Area (GTA) residents. For candidates residing outside the GTA, a remote workplace arrangement is available. Compensation Information Base salary range: $115,000 - $170,000. The final package will be commensurate with experience, skills, and geographic location (Canada). Includes a comprehensive benefits plan and a competitive incentive (bonus) program. #J-18808-Ljbffr