Senior AI Engineer

Toronto, ON
On-site
Posted Sep 27, 2026
1 position

Opens an external site

Employment type: Full-time
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level

Job summary

Design, build, and operate production-grade LLM and agentic AI applications, including RAG workflows and MCP server integrations, with secure, reliable, observable services. Collaborate with product, data, engineering, platform, and security teams to deliver business outcomes, shape technical direction, and promote engineering quality through mentoring and knowledge sharing.

Job details

Requisition ID: 274918 At Tangerine, we’re redefining banking. As Canada’s leading digital bank, we thrive on innovation, agility, and bold thinking, tackling every challenge head-on with leading technology and the unstoppable power of collaboration. Our client-obsessed teams deliver flexible, accessible banking solutions, breakthrough products, and award-winning service. Beyond banking, we’re committed to making an impact in the communities we serve and across our organization. We foster a culture built on integrity, inclusion, and fearless ambition – where diverse perspectives are valued, and people are empowered to do their best work. Are you ready to disrupt the status quo? Do you crave challenges that push boundaries? If you’re a high performer looking to accelerate your career and reimagine the banking landscape, this is your moment. Let’s shape the future of banking together! 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 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 Architect Secure, Reliable, And Observable 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 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 Mentor peers through code reviews and design discussions, raising the bar for quality, ownership, and long-term thinking Skills Do you have the skills that will enable you to succeed in this role? We'd love to work with you if you have: 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 Preferred Qualifications 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. Tangerine employees participate in Scotiabank’s pension & benefits programs (available to permanent employees) 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.

What you’ll do

Requirements

Requires extensive Python and data science library experience, hands-on development of LLM applications and MCP servers, full-stack and microservices fundamentals, and production experience with OAuth 2.0, OpenID Connect, and SAML. Candidates must also have strong data management knowledge and experience designing automated unit and functional testing; agentic AI frameworks, MLOps, classical machine learning, NLP and voice applications, Vertex AI, and React or Angular are preferred.