AI Engineer for Trading AI & Agent Tools (Hybrid)

Chicago Trading Company; Chicago (IL); Hybrid; USD 175,000 - 225,000; Full time

Job summary

Chicago Trading Company (CTC) is a premier proprietary trading firm focused on options market making. We build agent tooling, models, and infrastructure to empower engineers, quants, and traders across our systems.

The role involves integrating LLMs and agents into our ecosystem, drafting scalable solutions, and improving performance and reliability of shared services and model inference. Hybrid work is available in Chicago.

Qualifications

• Experience building software with LLMs and agents, including tools, context, orchestration, and model APIs.
• Familiarity with coding agents and the tradeoffs between models, providers, and harnesses.
• Comfortable working in Python, C++, and/or Java.
• Experience building software used by other engineers or end users.
• Demonstrated ability to take ambiguous problems from idea through production.
• Hands-on use of this technology outside of work.

Responsibilities

• Build agent tooling used by CTC's engineers, quants, and traders.
• Bring new models, coding agents, and agent harnesses into CTC as the ecosystem evolves.
• Build the common infrastructure needed to support them, including inference, configuration, integrations, tracing, and access controls.
• Build AI tools and interfaces for specific roles and workflows across the firm.
• Improve the performance and reliability of the systems we run, from shared services to model inference.
• Prototype new uses for agents in areas like research, simulation, and trading.
• Work directly with users to understand their workflows and guide what we build next.

Skills

LLM-based agents

Python

C++

Java

End-user software

Tools

LLM tools

Agent orchestration

Job description

Chicago Trading Company (CTC) is a premier proprietary trading firm focused on options market making. We build agent tooling, models, and infrastructure to empower engineers, quants, and traders across our systems.

The role involves integrating LLMs and agents into our ecosystem, drafting scalable solutions, and improving performance and reliability of shared services and model inference. Hybrid work is available in Chicago.