AI Enablement Engineer

DRW•Chicago, IL

1d•$175,000 - $225,000

About The Position

DRW is seeking AI Enablement Engineers for its newly formed AI Platform Team. The team has a dual mandate: provide low-friction access to leading AI tools while managing costs. The AI Platform Support & Enablement focus area supports adoption, user education, and firm-wide cost efficiency, complementing the engineering team that builds the platform rails. In this role, you will own the data-plane user experience and serve as the firm’s point of contact for AI tooling. You will support developers and business users of tools such as Cursor, Devin, ChatGPT, and LibreChat; help teams use models cost-effectively without sacrificing output quality; and relay user feedback to the AI Platform Engineering focus area. You will also promote effective and responsible use of enterprise AI tools through guidance, success stories, and workshops. The annual base salary range is $175,000 to $225,000, depending on experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. DRW offers employee benefits including medical, pharmacy, dental, and vision insurance; a 401(k) with discretionary employer match; short- and long-term disability; life and AD&D insurance; health savings accounts; and flexible spending accounts.

Requirements

Strong customer-facing communication skills and a white-glove support mentality.
Technical fluency in prompt engineering and a deep, practical understanding of current LLM capabilities, behaviors, and limitations.
Strong context of internal firm culture, user base, and existing support channels.

Nice To Haves

Familiarity with developer environments, IDEs such as VS Code and Cursor, and CLI tools such as Claude or Codex.

Responsibilities

Own the support queue for enterprise generative AI tools and troubleshoot IDE integrations, chat interfaces, and access issues.
Consult with high-spending teams on moving workloads from expensive proprietary models to less expensive mid-tier or internal open-weight models while maintaining output quality.
Review manual quota-increase requests triggered by the Management Plane and guide users in using internal dashboards to understand spending.
Identify weaknesses in tooling, prompt engineering, or model routing, and relay user pain points to the AI Platform Engineering focus area to inform the technical roadmap.
Promote and evangelize effective, responsible use of enterprise AI tools by helping users adopt AI golden paths, sharing success stories, and leading workshops.