Platform Engineer - AI Engineering

Location: Montreal

DRW  is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters-it's how we do it.  DRW  is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

The Team:
As AI tools drive immense value across the firm, our organization faces a  Dual Mandate : providing low-friction access to the best frontier AI tools while strictly managing an exponentially growing cost curve. The unified AI Platform Team builds the centralized software, operations, and governance layers that safely route users to the most cost-effective models.

The Role:

We are looking for a Platform Engineer to help build and operationalize our AI tooling ecosystem. Working closely with the Team Lead and Senior/Staff SWE, you will be the hands-on integrator connecting external cloud AI providers, internal models, and end-user tools into our unified control plane.

Key Responsibilities:

Configure and manage multi-engine API gateways, implementing dynamic routing rules, rate limits, and fallback logic for LLM requests.

Execute the technical migration and integration of firm-wide tools into our centralized management plane to ensure all AI traffic is securely logged and governed.

Operate within our Shared Responsibility Model alongside the Cloud team to manage AI services deployed in enterprise landing zones (e.g., managing Azure OpenAI instances, model deployments, and API key generation).

Write robust Go and Python code to support the continuous sync loop for our usage dashboard and implement automated  progressive friction  mechanisms, such as alerts.

Partner with the Inference Infrastructure pod to ensure our self-hosted, on-premise models are successfully registered and routable within our AI gateways.

Required Qualifications:

Strong backend programming experience, specifically in Go and/or Python.

Hands-on experience with API design, integration, and platform/cloud engineering concepts.

Familiarity with API gateways, proxy configuration, or distributed system networking.

A strong interest in the rapidly evolving LLM ecosystem and the technical mechanics of AI tooling.

A collaborative mindset with a focus on writing clean, maintainable code to replace prototype systems.

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