Lead AI Optimization

What you'll do

• Translate business needs into practical technical designs and guide initiatives from discovery through production readiness.
• Develop reusable tools and benchmarks for evaluating large language models and AI applications.
• Optimize model performance by improving prompting, retrieval, context construction, and serving approaches.
• Run structured experiments and A/B tests to validate improvements in quality, latency, and cost.
• Build critical software components, perform code reviews, and ensure production maintainability.
• Partner with cross-functional teams to resolve dependencies and communicate technical trade-offs to stakeholders.
• Mentor engineers and share reusable components, evaluation tooling, and practical AI guidance.

What we're looking for

• Bachelor's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent practical experience.
• Six or more years of experience in applied machine learning or AI engineering, including production LLM or model-serving systems.
• Advanced degree in a relevant field (preferred).
• Strong hands-on Python development skills and software engineering judgment for building maintainable production components.
• Experience evaluating LLMs and AI applications using representative datasets, scoring methods, automated tests, and failure analysis.
• Experience in prompt and retrieval optimization and model performance tuning to improve quality, latency, reliability, and cost.
• Experience in asset management, wealth management, or other financial-services AI applications (preferred).
• Experience with fine-tuning, preference optimization, quantization, or distillation of production models (preferred).