Senior Software Developer, LLM Infrastructure

Build something people love

Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.

We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work .

Machine Learning Infrastructure Team

The Machine Learning Infrastructure team builds the core foundation powering AI and GenAI initiatives across Wealthsimple. As our AI footprint expands, our priority is building scalable, cost-effective infrastructure that enables high-performance inference using open-source models alongside vendor solutions. Our responsibilities are to:

Build and maintain infrastructure to host and serve open-source LLMs reliably on cloud/GPU systems.

Implement intelligent model-routing frameworks to optimize performance, cost, and latency.

Develop evaluation and benchmarking tooling (Evals) to test, validate, and compare model performance across use cases.

Set the technical direction for operating scalable LLM infrastructure company-wide.

The Role

As a Senior Software Engineer on the ML Infrastructure team, you will design and implement the core backend and infrastructure powering our AI systems. You will work closely with data scientists, platform engineers, and engineering leaders to scale our GenAI footprint efficiently and securely.

In this role, you will have the opportunity to:

Build model-routing architecture (e.g., LiteLLM integration) to dynamically direct requests across internal and external models.

Provision and manage high-performance GPU infrastructure for serving open-source LLMs.

Build evaluation frameworks (Evals) that enable engineers and data scientists to benchmark model quality against production requirements.

Drive key cost-optimization and infrastructure efficiency initiatives without sacrificing system accuracy or reliability.

We are looking for people who have:

6+ years of software engineering experience building production-ready distributed systems or data platform infrastructure.

Strong proficiency in Python and infrastructure tooling like Kubernetes and Terraform .

Proven experience designing and operating highly performant, observable backend systems.

Practical experience or deep familiarity with the modern AI ecosystem (e.g., serving open-source models, vLLM, Ray, model routing, or evaluation frameworks).

Track record of owning technical projects end-to-end with high autonomy.

Our stack includes:

Container & Infra: Kubernetes, Terraform, AWS GPU infrastructure