Senior AI Engineer
20 hours ago
Winnipeg, Manitoba, Canada
Tangerine
Full-time
Free with email or Google
Save this job and keep your search organized
Create a free account to save jobs, create alerts and return to this listing from your dashboard.
Free with email or Google
By continuing, you agree to our Terms & Privacy Policy.
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 cou
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 cou