Staff AI Engineer - Tangerine

Tangerine Bank; Toronto; On-site; CAD 90,000 - 120,000; Full time

Job summary

Tangerine Bank is looking for a candidate to design and scale LLM-powered AI applications in Toronto. Key responsibilities include building secure systems, mentoring peers, and delivering impactful AI capabilities. Required qualifications include extensive experience in Python and data science libraries, hands-on experience with LLM applications, and strong full stack fundamentals. Preferred skills include knowledge of MLOps tools, classical machine learning algorithms, and modern web frameworks like React and Angular. We value diversity and accessibility in our working environment.

Qualifications

• Extensive experience in Python and core data science libraries (e.g., Scikit-learn, Pandas).
• Hands-on experience building LLM-powered applications.
• Strong experience in full stack fundamentals and microservices.

Responsibilities

• Design and build LLM-powered applications and AI solutions.
• Ensure systems are secure, reliable, and observable.
• Mentor peers and influence engineering culture.

Skills

Python programming

LLM-powered applications

API authentication and authorization

Automated testing

Data management

Tools

Docker

Git

React

Angular

Job description

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

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:

• 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)

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.