- Design, build, and own AI features to help users understand and manage their money.
- Work across the full spectrum of AI development, from prompt engineering and API integrations to building multi-agent systems and fine-tuning language models.
- Make critical decisions on conversational AI architecture and how to evaluate and ship AI features.
- Collaborate closely with the AI Platform team, focusing on the AI application layer.
- Apply GenAI and ML to help users make sense of their money, understanding spending patterns, surfacing actionable insights, or automating financial tasks.
- Choose the right AI toolkit thoughtfully, balancing innovation with pragmatism to ship features that work reliably at scale.
- Leverage and enhance the sophisticated evaluation framework to ensure AI quality, designing test datasets, implementing new scorers, and validating changes before release.
- Own AI feature development, agent design and orchestration, ML model improvements, evaluation datasets and scorers, prompt engineering, and feature-level quality.
PythonMachine LearningPrompt Engineering