Senior AI Risk Researcher, AI.x

Your Opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together. We believe in the power of collaboration and value being together in the office, which is why this role is based on-site in our San Francisco office. Joining Schwab means joining a company committed to transforming the financial industry and putting clients at the center of everything we do.

 

Schwab Technology Services enables the future of how clients manage their money by providing innovative and reliable technology products and services as part of our ongoing commitment to democratize access to investing and financial planning.

Schwab’s AI Strategy & Transformation team, known as AI.x, is the central hub for Artificial Intelligence at Schwab. We are an integrated product, engineering, strategy and risk team, all based in San Francisco. We help set the enterprise vision for AI, invest in the most promising opportunities, and accelerate delivery across the company. We also build the core platform that powers AI at scale and explore next-generation GenAI efforts that will redefine how we serve our clients. As an AI Researcher on AI.x, you will play a key role in bringing these priorities to life by advancing cutting-edge AI research and developing innovative solutions.

 

This role is more than a research position. It is an opportunity to join a high-profile team shaping Schwab’s future with AI, to conduct research that directly influences how AI systems are built and deployed, and to help establish industry-leading practices for responsible AI. As a Senior AI Risk Researcher, you will investigate the risks and failure modes of generative AI systems and agents, with a particular focus on human-centered harms. You will collaborate with compliance, risk and legal to design research programs and evaluation methodologies that examine how AI systems behave under realistic and adversarial conditions; lead risk investigations and red-teaming exercises; and translate findings into practical recommendations for researchers and product teams.

Your work will help identify risks such as misinformation, inappropriate advice, bias, manipulation, harmful content generation and other emerging issues, while engineering teams typically own implementation of technical mitigations, evaluations, and guardrails. You will also s trengthen scientific practices, contribute to Schwab’s responsible AI strategy, and bring curiosity, creativity, sound judgment, and a deep appreciation for the human impact of AI systems to help shape the next generation of AI at Schwab.

What you have

Required Qualifications:

• A master’s or other advanced degree in Computer Science, Cognitive Science, Psychology, Sociology, Philosophy, Human-Computer Interaction, Linguistics, Public Policy, Statistics, Law, or a related field, or equivalent industry experience.
• 8+ years of experience conducting research involving technology, human behavior, decision-making, risk analysis, or related disciplines.
• 5+ years of experience working with AI systems, machine learning applications, or digital platforms that impact users at scale.
• Experience designing and executing rigorous qualitative, quantitative, or mixed-methods research.
• Demonstrated ability to identify, analyze, and communicate complex risks involving technology or AI systems.
• Experience translating research findings into practical recommendations for product, engineering, business, or governance stakeholders.
• Strong written and verbal communication skills, with the ability to explain complex concepts to both technical and non-technical audiences.

Preferred Qualifications:

• Experience conducting AI red teaming, adversarial testing, trust and safety research, responsible AI assessments, or related evaluations.
• Expertise in one or more areas including fairness, harmful content, misinformation, or behavioral manipulation.
• Experience developing methodologies that uncover subtle or unexpected AI failure modes.
• Experience at a financial institution.
• Strong analytical and data science fundamentals, including the ability to structure investigations and analyze research findings.
• Experience working with multidisciplinary teams spanning research, engineering, product, legal, compliance, and risk functions.
• Curiosity about emerging technologies and their potential impact on clients in the context of financial institutions.