AI Engineer
- Chicago, United States +1
- Posted
As a Quantitative Technologist, your goal is to enhance live trading systems, research infrastructure, and alpha generation through technology innovation.
We leverage cutting-edge software and hardware (mostly with modern C++) to push production level code daily and evolve fully-automated strategies, alpha generation processes, live trading systems, and machine learning research and simulation infrastructure used to analyze petabytes of data.
The Role
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 (utilizing 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 core metrics across agent systems, focusing on reasoning quality, retrieval accuracy, latency, cost, safety, and user experience
About You
5+ years of overall technical experience, including 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 alongside solid software engineering principles and a deep understanding of the full AI/ML lifecycle (data prep through observability)
Expert familiarity with agentic frameworks and modern AI orchestration and development tools (e.g., LangChain, LangGraph, AutoGen, LlamaIndex) alongside deep practical skills in prompt engineering
Proven capability to evaluate and select foundational or open-weight models, balancing enterprise trade-offs across capability, context length, hosting, security, and cost
COMPENSATION – Competitive base salary, plus quarterly bonus based on individual performance and contribution towards success of others and the firm.
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