Senior Applied Scientist, Wealth.com

• A degree in Computer Science, Engineering, or a related quantitative field (or equivalent practical experience)
• Proven experience building and shipping software in a production environment. You are a builder at heart and have a portfolio of projects (personal or professional) that have seen real user traffic
• Strong software engineering fundamentals, including data structures, algorithms, system design, and writing clean, maintainable code
• Hands-on experience building, deploying, and maintaining production-level agent systems using frameworks like Agent Development Kit (ADK) or LangGraph
• Proficiency in Python and a strong aptitude for working in a polyglot environment that may include TypeScript, C#, etc
• Experience developing applications that consume and integrate APIs from major AI providers (e.g., Google Vertex AI, Azure OpenAI)

Desirable

• We are seeking an Applied Scientist with a strong software engineering foundation to build the next generation of legal and financial AI
• In this role, you will move beyond theoretical knowledge and focus on the practical application of building, scaling, and maintaining robust, production-grade AI systems
• You will work on a variety of initiatives, from complex document understanding to the development of sophisticated AI agents that will redefine how estate planning is done
• Your primary focus will be on the "how"—how to effectively leverage state-of-the-art models in a real-world application, how to build scalable and secure systems around their limitations, and how to ship products that deliver real value to our users
• Design, build, and deploy production-grade systems leveraging Large Language Models (LLMs) from providers like OpenAI, Google (Vertex AI), and Anthropic
• Develop and scale end-to-end applications for complex document understanding, focusing on textual, financial, and tabular data. This includes building sophisticated, high-precision RAG (Retrieval-Augmented Generation) systems that are battle-tested for production traffic
• Implement robust guardrails, validation layers, and monitoring to preemptively address model limitations, such as hallucinations, both in offline evaluation and online production environments
• Engineer and deploy complex, multi-step AI agents, with a focus on creating agentic workflows that are scalable, maintainable, and secure, especially when handling highly sensitive client data
• Own projects from conception to deployment, making key architectural decisions and ensuring the systems you build meet stringent requirements for latency, precision, and recall
• Build scalable ETL (Extract, Transform, Load) data pipelines to process and prepare complex datasets for AI model consumption
• Collaborate closely with product managers, software engineers, and other scientists to build tools, define metrics, and continuously improve the end-to-end quality of our AI systems
• Align your technical work with business outcomes, effectively communicating the impact and performance of the systems you build to stakeholders