Senior AI Engineer - Tangerine

Scotiabank•Toronto, ON

23h•Onsite

About The Position

Tangerine is Canada’s leading direct bank, offering 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.

Requirements

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
Hands-on experience building and consuming MCP servers (designing endpoints, schemas, access boundaries)
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

Nice To Haves

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)

Responsibilities

Design, build, and productionize LLM-powered and agentic applications, including retrieval-augmented generation (RAG), multi-step reasoning workflows, structured outputs, and prompt safety
Build and consume MCP servers, defining schemas, endpoints, and access boundaries that enable safe, scalable tool use
Work hands-on to de-risk complex problems by writing, reviewing, and operating production-grade AI systems
Partner closely with product, data, and engineering stakeholders to deliver AI capabilities that drive tangible outcomes
Apply strong fundamentals in structured and unstructured data, distributed systems, and service integration
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 and security partners to ensure systems meet enterprise risk, compliance, and operational standards
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
Mentor peers through code reviews and design discussions, raising the bar for quality, ownership, and long-term thinking