Job description

Core Responsibilities Performs manual and AI-assisted secure code reviews across modern application stacks, analyzing source code to identify vulnerabilities, logic flaws, and insecure coding practices. Develops and optimizes prompts, workflows, and review methodologies that improve the effectiveness and repeatability of AI-assisted code review activities. Validates and refines vulnerability findings, reducing false positives and identifying overlooked risks. Produces clear technical reports and risk-based recommendations. Partners with development teams to explain findings, assess risk, and provide actionable remediation guidance. Collaborates with penetration testers, threat modelers, and application security teams. Contributes to team processes, methodologies, and automation initiatives. Required Qualifications Minimum of 5 years of related work experience in application security, secure code review, or software engineering with a security focus. Strong understanding of secure coding principles, application security vulnerabilities (OWASP Top 10 and common application vulnerabilities), and secure software development practices. Understanding of modern software architectures, APIs, cloud-native applications, and CI/CD pipelines. Experience reviewing Java, C#, Python, JavaScript/TypeScript, Go, or similar languages. Experience using SAST tools such as Checkmarx, Fortify, Veracode, Semgrep, or SonarQube as well as familiarity with secure SDLC and DevSecOps practices Hands-on experience using generative AI or AI-assisted developer/security tools as part of engineering, code review, security testing, or DevSecOps workflows. Ability to communicate security findings and remediation guidance to developers and technical leadership Undergraduate degree in a related field or an equivalent combination of training and experience. Preferred Qualifications Experience creating prompts, workflows, agents, or automations. Experience leveraging large language models (LLMs) to improve security analysis, code review efficiency, vulnerability triage, or secure development workflows. Familiarity with LLM security risks, prompt injection, insecure code generation, model misuse, and AI application attack vectors. Experience reviewing applications that utilize machine learning, generative AI, agentic AI, or AI-enabled business processes. Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don t just have a mission—we re on a mission. To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best. How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

Requirements

Must-haves

Performs manual and AI-assisted secure code reviews across modern application stacks, analyzing source code to identify vulnerabilities, logic flaws, and insecure coding practices.
Develops and optimizes prompts, workflows, and review methodologies that improve the effectiveness and repeatability of AI-assisted code review activities.
Validates and refines vulnerability findings, reducing false positives and identifying overlooked risks.
Produces clear technical reports and risk-based recommendations.
Partners with development teams to explain findings, assess risk, and provide actionable remediation guidance.
Collaborates with penetration testers, threat modelers, and application security teams.
Contributes to team processes, methodologies, and automation initiatives.
Minimum of 5 years of related work experience in application security, secure code review, or software engineering with a security focus.
Strong understanding of secure coding principles, application security vulnerabilities (OWASP Top 10 and common application vulnerabilities), and secure software development practices.
Understanding of modern software architectures, APIs, cloud-native applications, and CI/CD pipelines.
Experience reviewing Java, C#, Python, JavaScript/TypeScript, Go, or similar languages.
Experience using SAST tools such as Checkmarx, Fortify, Veracode, Semgrep, or SonarQube as well as familiarity with secure SDLC and DevSecOps practices
Hands-on experience using generative AI or AI-assisted developer/security tools as part of engineering, code review, security testing, or DevSecOps workflows.
Ability to communicate security findings and remediation guidance to developers and technical leadership
Undergraduate degree in a related field or an equivalent combination of training and experience.

Nice-to-haves

Experience creating prompts, workflows, agents, or automations.
Experience leveraging large language models (LLMs) to improve security analysis, code review efficiency, vulnerability triage, or secure development workflows.
Familiarity with LLM security risks, prompt injection, insecure code generation, model misuse, and AI application attack vectors.
Experience reviewing applications that utilize machine learning, generative AI, agentic AI, or AI-enabled business processes.
Special Factors
Vanguard is not offering visa sponsorship for this position.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aici/cdjavapythonjavascripttypescriptgollmmachine learning

Platform: workday
Effort: long