Platform Engineer - AI Engineering

Description

The company is a diversified trading firm with 3+ decades of experience combining advanced technology and strong people to trade in markets worldwide, using its own capital and bearing its own risk.

Headquartered in Chicago, with offices across the U.S., Canada, Europe and Asia, it trades Fixed Income, ETFs, Equities, FX, Commodities and Energy in all major global markets, and runs three non-traditional strategies: real estate, venture capital and cryptoassets.

The company values respect, curiosity and open minds, high standards, integrity, innovation, and being willing to question the prevailing view.

The AI Platform Team is a single group that builds the central software, operations and governance layers that direct users to the most cost-effective models. Its job is to keep access to leading frontier AI tools easy for staff while controlling a cost curve that is growing exponentially.

Responsibilities

• Help build and roll out the firm's AI tooling, working directly with the Team Lead and Senior and Staff software engineers.
• Act as the hands-on link between external cloud AI providers, internal models and end-user tools, all feeding one control plane.
• Set up and run multi-engine API gateways, including dynamic routing, rate limits and fallback logic for LLM requests.
• Move firm-wide tools onto the central management plane so every AI request is securely logged and governed.
• Share operational duties with the Cloud team under the Shared Responsibility Model for AI services in enterprise landing zones, such as Azure OpenAI instances, model deployments and API key creation.
• Write dependable Go and Python code for the continuous sync that feeds the usage dashboard, and build automated progressive friction controls, such as alerts.
• Work with the Inference Infrastructure pod so self-hosted, on-premise models are registered and can be routed through the gateways.

Requirements

• Solid backend programming experience in Go, Python or both.
• Hands-on experience with API design, integration, and platform or cloud engineering.
• Familiarity with API gateways, proxy configuration or distributed system networking.
• A genuine interest in how the fast-moving LLM ecosystem and AI tooling work underneath.
• A collaborative approach and the discipline to write clean, maintainable code that replaces prototype systems.