Radix Trading LLC
AI Engineer
Requirements
Candidates must have at least 5 years of technical experience, including 2 years specifically in Generative AI or LLM application development. A degree in Computer Science, Data Science, Machine Learning, or a related field is required, along with strong proficiency in Python and software engineering principles.
Responsibilities
You will build and accelerate the firmwide AI ecosystem by designing and deploying production-grade AI applications and agentic workflows. Additionally, you will identify workflow opportunities for automation and develop platform-level safeguards to ensure system reliability and performance.
About the role
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.