AI Software Engineer

Role overview

Responsibilities

• Build agentic decision-support systems that reason over data, use models and assist complex human decisions.
• Develop evaluation frameworks, feedback loops and benchmarks to find failures and validate improvements.
• Set measurable objectives, analyze performance distributions and separate real improvement from metric shifts.
• Explore self-improving agent architectures, adaptive tool selection and policy improvement.
• Apply statistical modeling and AI/ML to improve reliability and usability.
• Use AI coding systems to produce high-quality software.
• Own work from problem formulation through design, implementation, evaluation and deployment.
• Challenge assumptions and optimize solutions through rigorous analysis.
• Explain complex ideas, assumptions and limitations to technical and business stakeholders.

Required qualifications

• Strong quantitative foundation in mathematics, physics, statistics, engineering or a related field.
• Hands-on experience designing or developing agentic systems, including multi-step reasoning and planning.
• Proficiency in statistical modeling and AI/ML algorithms, uncertainty, validation and experiment design.
• Ability to produce high-quality software with AI coding systems, with attention to architecture and code quality.
• Strong analytical and problem-solving skills; comfortable questioning assumptions and redefining problems.

Preferred qualifications

• Decision science, causal inference or optimization experience is preferred.
• Familiarity with reinforcement learning, simulation or adaptive experimentation is preferred.
• Knowledge of agent evaluation and performance improvement is preferred.
• Experience in complex enterprise decision environments such as finance, insurance or logistics is preferred.
• A master's or PhD in a quantitative discipline is preferred; candidates with a bachelor's degree and strong analytical skills may be considered.
• Comfort with mathematical reasoning about unfamiliar problems and curiosity about complex systems are expected.

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