AI Application Security Engineer

Job Description Assist in building and enhancing an AI-driven harness for application security vulnerability detection Develop Python-based components to support AI-powered AppSec testing workflows Leverage AI tools and models to identify, analyze, and prioritize application security vulnerabilities Collaborate with engineering and security teams to integrate AI-driven solutions into development pipelines Evaluate strengths and weaknesses of different AI models for software security use cases Contribute to building internal application security capabilities and tooling Continuously test, iterate, and improve AI-based approaches to security testing and detection We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: Skills and Requirements 5+ years of software development experience with strong emphasis on JavaScript and Python Strong Python development skills with hands-on experience building and scaling applications Proven background in Application Security (AppSec) including vulnerability identification and mitigation Experience leveraging AI/ML in software development or security use cases Understanding of AI model capabilities, limitations, and practical application in security workflows Experience building or contributing to tools/platforms for application security testing Ability to work autonomously and contribute to building internal security capabilities (AI harness, tooling) Experience building AI-driven security testing frameworks or “AI harness” tools Familiarity with internal platforms or security capability building (e.g., Mythos-like systems) Exposure to DevSecOps practices and secure SDLC integration Experience with LLMs, prompt engineering, or evaluating AI model effectiveness Background in automation of application security testing processes Experience working in financial services or highly regulated environments Insight Global