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AI Engineer

Job in Vancouver, BC, Canada
Listing for: Saxo Bank
Full Time position
Listed on 2026-02-28
Job specializations:
  • Software Development
    AI Engineer, Cloud Engineer - Software, Software Engineer, Backend Developer
Job Description & How to Apply Below
Copenhagen, Denmark

We are hiring for our AI Engineering team. This role is about building and operating AI‑powered products and services — primarily customer‑facing features for our trading platforms, but also internal tools used widely across the company. The work is hands‑on, production‑oriented and varied. The role is based at our headquarters in Denmark.

The team works with the latest models, tools and protocols as they emerge and apply them to real products used by clients. There is a high degree of autonomy in how we work and what we build, and genuine room to shape the role and make an impact. We are a small team relative to the scope of what we do, which means your work matters and your ideas get heard.

We build on top of large language models through APIs and SDKs. The work is engineering: integrating, orchestrating and building reliable systems around AI capabilities. You will work with product managers, designers and engineers across the company to ship AI features that meet real needs and run well in production. The tech stack is primarily Python, Type Script and C#, deployed as containerized services on our Kubernetes clusters.

What you will do

Build customer‑facing AI features such as conversational assistants, intelligent search, personalised insights, and platform assistance.

Develop and maintain internal AI tools for knowledge retrieval, summarisation, research and workflow automation.

Design and implement agentic systems, i.e. multi‑step AI workflows using tool‑calling, context management and orchestration to solve complex tasks.

Work directly with model provider APIs and SDKs. We prefer lean integrations over heavy frameworks, and expect you to be comfortable working close to the API level.

Build and maintain integrations with data sources and services (SQL, REST APIs, event‑driven systems); handle data ingestion and PII appropriately.

Integrate emerging standards and protocols such as MCP (Model Context Protocol) and A2A (Agent‑to‑Agent) with our services and platforms.

Ship production services on Kubernetes with Docker; set up CI/CD pipelines, automated testing, observability and rollback strategies.

Contribute to shared SDKs, templates and best practices used by teams across the organisation.

Work with Information Security, Legal, Compliance and Data Protection on privacy, security and responsible AI.

Keep things running: code reviews, incident response, capacity planning and clear documentation.

Your profile
You are a pragmatic engineer who ships working software and takes ownership of what you build. You are comfortable working across the stack and across disciplines — whether that means backend services, front‑end work, Dev Ops, or sitting down with a product manager to shape requirements. We value breadth and curiosity over deep specialisation in any single area.

Strong in at least one of Python, Type Script or C#. If you have a degree of familiarity with more than one, that is a plus.

Experience building production APIs, services or applications. You know what it takes to keep software running reliably.

Practical experience working with large language models: prompt engineering, tool/function calling, context engineering, or building agentic workflows.

Comfortable working directly with model APIs and provider SDKs rather than relying on high‑level abstraction frameworks.

Comfortable using AI‑assisted development tools in your daily work and collaborating effectively with AI throughout the development process.

Security and privacy awareness, including risks specific to LLM‑based systems such as prompt injection and data leakage.

Clear written and verbal communication in English.

Nice to have, but not required

Full‑stack experience, including front‑end or UI/UX work.

Hands‑on experience with AI safety, guardrails or content filtering in production systems.

Experience with cloud platforms such as Azure, GCP or AWS.

Dev Ops skills: infrastructure as code, container orchestration, CI/CD.

Background in product thinking, business analysis or technical enablement.

Experience contributing to developer tooling, SDKs or internal platforms.

We review applications on an ongoing basis. If this role matches…
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