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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 newly formed AI Platform Team owns this unified mission. While the engineering side of our team builds the platform rails, the AI Platform Support & Enablement focus area acts as the crucial "human-in-the-loop." We are dedicated to ensuring high user velocity and frictionless adoption of AI tools while actively managing firm-wide cost efficiency and user education.

The Role

We are seeking AI Enablement Engineers to own the data plane user experience. You will be the face of AI tooling for the firm, supporting developers and business users who use tools such as Cursor, Devin, ChatGPT, and LibreChat.

Key Responsibilities

• Own the support queue for enterprise generative AI tools. Troubleshoot IDE integrations (Cursor, Devin), chat interfaces, and access issues.
• Actively consult with high-spending teams to safely "downshift" their workloads from expensive proprietary models (like Claude Opus) to cheaper mid-tier or internal open-weight models without degrading output quality.
• Review manual quota-increase requests triggered by the Management Plane and guide users through spend visibility via internal dashboards.
• Identify weaknesses in tooling, prompt engineering, or model routing, and feed user pain points directly to the AI Platform Engineering focus area to inform the technical roadmap.
• Promote and evangelize effective, responsible use of enterprise AI tools, for example, by helping users understand and adopt AI 'golden paths', sharing success stories, and leading workshops.

Required Qualifications