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Added 6 mins ago
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Tangerine

Senior AI Engineer

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 25, 2026
Posting language: English
Posted: Sep 25, 2026

Apply About employer

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Original job description

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.

Apply About employer

More about this job

Responsibilities

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.

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.

Skills

Python
Scikit-Learn
Pandas
NumPy
Large Language Models
Retrieval-Augmented Generation
Agentic AI
MCP Servers
Microservices
OAuth 2.0
OpenID Connect
SAML
Automated Testing
MLOps
Machine Learning
Natural Language Processing

Benefits

Pension
Employee Benefits
Career Development Courses
Workspace Flexibility

Visa sponsorship

Not detected in the job text

Keywords

Python
Scikit-Learn
Pandas
NumPy
Matplotlib
Seaborn
Large Language Models
Agentic AI
Retrieval-Augmented Generation
MCP Servers
Prompt Safety
Structured Outputs
Multi-Step Reasoning
Microservices
OAuth 2.0
OpenID Connect
SAML
Automated Testing
Unit Testing
Functional Testing
MLOps
Docker
CI/CD
Machine Learning
Fraud Detection
Credit Risk Scoring
Natural Language Processing
IVR
Vertex AI
React

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