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

Robust 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.

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📌 Staff AI Engineer - Tangerine (Ontario)
🏢 Tangerine Bank
📍 Ontario