AI Application Security Engineer

Charles Schwab Inc.•Southlake, TX

1d•$130,000 - $160,000•Onsite

About The Position

At Schwab, this role helps protect predictive, generative, and agentic AI capabilities throughout the software development lifecycle. The Senior Application Security Engineer focused on AI security designs scalable security standards, architectures, testing capabilities, monitoring solutions, and guardrails for AI-enabled applications, models, APIs, and software supply chains. The engineer works with development, architecture, platform engineering, and security teams to assess emerging threats, evaluate complex risks, and translate findings into practical solutions. The role also builds and maintains internal AI security libraries for prompt-input validation, output protection, redaction, PII safeguards, and automated testing. By integrating these capabilities into developer workflows, common frameworks, and CI/CD pipelines, the engineer enables teams to remediate vulnerabilities, make informed security decisions, and deliver secure AI capabilities at scale. The selected candidate is expected to work on site in the specified location(s). The role is eligible for bonus or incentive opportunities in addition to the salary range.

Requirements

5+ years of experience in application security, security engineering, software engineering, or a related cybersecurity discipline.
Experience implementing and governing secure software development lifecycle practices.
Experience with application security, API security, authentication and authorization, threat modeling, vulnerability management, and software supply chain security.
Experience with cloud platforms, CI/CD pipelines, automation, and modern application architecture.
Proficiency in Python, Java, C#, Go, JavaScript, or another programming language.
Exposure to cloud AI/ML frameworks, including AWS Bedrock, Azure OpenAI, or Google Cloud Vertex AI.
Familiarity with GitHub and CI/CD tools.
Working knowledge of HTTP protocols, HTTP proxies, and core networking concepts.
Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience.

Nice To Haves

Experience securing generative AI, large language models, agentic AI platforms, or machine learning systems.
Experience using large language models to develop agents, create AI harnesses, or solve business problems.
Knowledge of prompt injection, model abuse, model poisoning, data leakage, excessive agency, and related AI threats.
Familiarity with the OWASP Top 10 for Large Language Model Applications, NIST AI Risk Management Framework, or MITRE ATLAS.
Experience with security testing, observability, and production monitoring.
Demonstrated ability to evaluate complex risks, make sound decisions, and develop scalable security solutions.
Ability to communicate technical risks and collaborate across development, architecture, platform engineering, and security teams.
CISSP, CSSLP, cloud security, AI security, or another relevant industry certification.

Responsibilities

Protect predictive, generative, and agentic AI capabilities throughout the software development lifecycle.
Design scalable security standards, architectures, testing capabilities, monitoring solutions, and guardrails for AI-enabled applications, models, APIs, and software supply chains.
Work with development, architecture, platform engineering, and security teams to assess emerging threats and evaluate complex risks.
Translate security findings into practical solutions.
Build and maintain internal AI security libraries, including prompt-input validation, output protection, redaction, PII safeguards, and automated testing.
Integrate AI security capabilities into developer workflows, common frameworks, and CI/CD pipelines.
Enable teams to remediate vulnerabilities, make informed security decisions, and deliver secure AI capabilities at scale.