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.

Do you like new challenges? Are you ready to reach new heights in your career and become part of an established disruptor? If so, come join us and help redefine the Canadian banking landscape!

Is this role right for you? In this role, you will:
Deliver and Scale Agentic AI Solutions:
Serve as the technical lead and primary engineering point person for AI use cases within the focus area, owning technical decomposition, delivery coordination, dependency management, and execution quality from concept through production
Build partnerships with business domains to demonstrate the art of possible and translate business requirements to delivery timelines and features
Design, build, and productionize LLM-powered and agentic applications, including retrievalaugmented generation (RAG), multi-step reasoning workflows, structured outputs, and prompt safety
Work hands-on to de-risk complex problems by writing, reviewing, and operating production-grade AI systems

Architect Secure, Reliable, and Observable Systems

Align use case design with platform patterns, governance expectations, and operational support models
Ensure systems are testable, observable, and resilient, with automated testing and clear operational feedback loops
Design and operate secure, low-latency services and microservices with modern authentication and authorization
Contribute to architectural discussions, platform capabilities, and evolving best practices for AI development
Collaborate with platform, security, and risk partners to ensure systems meet enterprise compliance, operational, and governance standards

Influence Technical Direction and Engineering Culture

Take ambiguous problems and translate them into clear technical solutions, communicating trade-offs and constraints
Model a culture of engineering excellence, inclusion, and continuous learning — digging into root causes and sharing durable lessons
Influence technical direction beyond the immediate team by contributing reusable patterns, engineering standards, and architectural guidance across AI initiatives
Mentor peers through code reviews and design discussions, raising the bar for quality, ownership, and long-term thinking

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:
Experience leading complex AI initiatives across multiple stakeholders from business case through production rollout
Ability to make sound technical trade-offs across speed, risk, scalability, and maintainability
Experience in AI safety, evaluation, and responsible AI practices
Strong communicator with the ability to manage relationships, align stakeholders, and navigate dependencies across projects and products
Extensive experience in Python and its core data science libraries (e.g., Scikit-learn, Pandas, NumPy, Matplotlib/Seaborn)
Hands-on experience building LLM-powered applications — retrieval, agents, structured outputs, prompt safety
Strong experience in full stack fundamentals and microservices. Production experience with API authentication and authorization (OAuth 2.0, OpenID Connect, and SAML) is required
Deep understanding of structured and unstructured data management and their corresponding technologies
Proven experience in automated testing, including unit and functional testing, and the ability to develop test strategies and design automation frameworks

Preferred Qualifications:
Served as tech lead for an AI driven product and established partnership with product management
Experience with Agentic AI frameworks and designing multi-step AI reasoning processes - 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
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
Experienced with building and deploying NLP and voice response applications (including IVR and contact center intelligence)
Familiarity with Google's Vertex AI tech stack
Experience building applications with modern web component frameworks (such as React & Angular)

What's in it for you?

You will be part of a diverse and inclusive team of Client-focused go-getters looking to learn from each other in an environment that celebrates and recognizes success!
You will have access to thousands of online and in-person courses so you can shape your career growth with support from diverse industry leaders.
You will get our help to save for your future and to invest in your total well-being through our Tangerine benefits.
You belong here, and we are equal and uncomplicated. Bring your true self to work, dress codes don’t apply here.
You will enjoy workspace flexibility and all the excitement that comes from working at the official Bank of the Toronto Raptors.

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.