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

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.