Principal AI Engineer - Tangerine at Scotiabank

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

15 Aug, 26

Salary

0.0

Posted On

17 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Agentic AI, Python, LLM Production, System Design, MLOps, Full Stack Development, Vector Search, Microservices, OAuth 2.0, CI/CD, Feature Engineering, RAG, Vertex AI, React, Angular, Kubernetes

Industry

Banking

Description

Requisition ID: 261887 Tangerine is Canada’s leading direct bank. We offer flexible and accessible banking options, innovative products, and award-winning Client service. The reason why Tangerine employees come to work each day is to help Canadians live better lives. We focus on making a difference in our communities, and that includes our own internal community. It’s important to us that our employees feel empowered and enthusiastic about belonging to our Orange culture. Is this role right for you? In this role, you will: Strategy Development Work with the business to define and implement a strategy for personalizing natural language interfaces Act as lead engineering partner to translate business requirements into architectural patterns and best practices for agentic AI development Partner with Data, security, risk, and engineering teams to embed AI-driven resiliency, observability, and threat modeling into architecture standards Architecting Agentic Development Platform and Practice Work as part of a team defining and delivering the strategy and technical components and patterns for an agentic AI ecosystem Design and implement secure, resilient, and compliant AI platforms that integrate with existing enterprise systems, ensuring alignment with risk, ethics, and regulatory frameworks Build on knowledge of event driven architecture, message queues, and distributed systems to build resilient and scalable workflows in a secure and compliant manner Drive search and retrieval architecture, including vector-based search systems, indexing strategies, and relevance optimization Architect and implement scalable services and user-facing workflows across frontend and backend using agentic skills and tools Manage and iterate on new platform capabilities while balancing the needs of key projects delivering maintainable, scalable, testable, and easy to refactor Work hands-on and de-risk the critical parts of our complex projects. The role will be deeply involved in coding, reviewing, and optimizing AI solution Mentor and Drive Engineering Culture Inspire and mentor teams across architecture and engineering disciplines, cultivating a culture of innovation, responsibility, and trust in AI adoption. Drive next generation testing and observability practices for dynamic orchestration of user journeys Championing a culture of excellence, inclusion, and continuous learning within the team. When something breaks, you're not satisfied with a workaround. You dig until you understand why, and you bring learning and long-term solutions back to the team. Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have: Required Qualifications: Proven experience in AI leadership and delivery roles, with a track record of successfully leading and delivering AI projects going through scoping ambiguous problems, communicating trade-offs, and iterating based on real-world feedback Extensive experience in Python and its core data science libraries (e.g., Scikit-learn, Pandas, NumPy, Matplotlib/Seaborn). Hands-on experience building and taking LLM-powered applications to production (retrieval, agents, structured outputs, prompt safety) Experience with Agentic AI frameworks and designing multi-step AI reasoning processes Strong experience in full stack fundamentals and system design and integrations with demonstrated leadership and experience in designing and managing low latency microservices at scale withn authentication and authorization (experience in using OAuth 2.0, OpenID Connect, and SAML) Experience with MLOps principles and tools for model versioning (e.g., Git), containerization (e.g., Docker), and continuous integration/continuous deployment (CI/CD) of machine learning models Proven experience in automated testing and the ability to develop test strategies and design automation frameworks Demonstrated expertise in feature engineering, feature selection, and data transformation techniques for structured and unstructured data Preferred Qualifications: Strong theoretical and practical knowledge of classical machine learning algorithms (e.g., classification, regression, clustering, dimensionality reduction) and their applications in areas such as fraud detection, credit risk scoring, or customer segmentation Experience in Fine Tuning LLMs, embedding models, and tackling advanced RAG or agentic use cases Experienced with building and deploying NLP and voice response applications (including IVR and contact center intelligence) Experience in designing AI observability, monitoring systems, feedback loops, and trend analysis Familiarity with Google's Vertex AI tech stack Experience building applications with modern web component frameworks (such as React & Angular) Experience with containerized tooling and cloud platforms (particularly Docker/Docker Compose, Kubernetes, and GCP) Location(s): Canada : Ontario : Toronto At Tangerine we value the unique skills and experiences each individual brings to the team, and are committed to creating and maintaining an inclusive and accessible environment. If you require accommodation during the recruitment and selection process, please let our Recruitment team know.

Responsibilities

Lead the strategy and architectural design for personalizing natural language interfaces and agentic AI ecosystems. You will be responsible for building secure, scalable AI platforms and mentoring engineering teams to foster a culture of innovation.