AI Engineer

Radix Trading Experienced Job Board•Chicago, IL

About The Position

As a Quantitative Technologist, the AI Engineer enhances live trading systems, research infrastructure, and alpha generation through technology innovation. The firm uses modern software and hardware, mostly modern C++, to deliver production code and develop automated strategies, alpha generation processes, live trading systems, and machine-learning research and simulation infrastructure for analyzing petabytes of data. The AI Engineer builds and accelerates the firmwide AI ecosystem and infrastructure for AI-native systems and tooling. The role identifies opportunities to introduce AI-first systems and automation into developer and researcher workflows, and designs, deploys, and evaluates production-grade AI applications and agentic workflows using techniques such as RAG, semantic search, planning, and structured outputs. It also develops platform safeguards and optimizes agent-system performance, safety, cost, and user experience.

Requirements

  • At least 5 years of overall technical experience, including at least 2 years of hands-on experience designing and building Generative AI/LLM applications in production.
  • Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Machine Learning, or a related technical field.
  • Strong proficiency in Python, solid software engineering principles, and a deep understanding of the full AI/ML lifecycle, from data preparation through observability.
  • Expert familiarity with agentic frameworks and modern AI orchestration and development tools such as LangChain, LangGraph, AutoGen, and LlamaIndex, alongside deep practical prompt-engineering skills.
  • Proven ability to evaluate and select foundational or open-weight models, balancing enterprise trade-offs across capability, context length, hosting, security, and cost.

Responsibilities

  • Build and accelerate the firmwide AI ecosystem and infrastructure to support AI-native systems and tooling.
  • Identify workflow opportunities for developers and researchers to introduce AI-first systems and automation.
  • Design, deploy, and evaluate production-grade AI applications and advanced agentic workflows, including RAG, semantic search, planning, and structured outputs.
  • Develop platform-level safeguards, including bespoke evaluation harnesses, guardrails, approval workflows, tool-use limits, source attribution, and kill switches.
  • Optimize agent-system metrics, including reasoning quality, retrieval accuracy, latency, cost, safety, and user experience.

Benefits

  • Competitive base salary.
  • Quarterly bonus based on individual performance and contribution toward the success of others and the firm.
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