DevSecOps Full Stack Security Engineer

• Design build test deploy and maintain full-stack security products including user interfaces APIs web services data layers and cloud-based components.
• Apply AI/ML and AI-assisted technologies where appropriate to automate security processes and improve areas such as vulnerability triage risk assessment anomaly detection and self-service security workflows.
• Develop clean secure well-tested maintainable code following secure coding principles and software engineering best practices.
• Participate in solution architecture design and code reviews ensuring Zero Trust principles and DevSecOps controls are incorporated into product design and implementation.
• Collaborate with security DevSecOps product delivery and platform engineering teams to translate product roadmaps and security requirements into technical deliverables.
• Design and implement continuous integration and continuous delivery (CI/CD) pipelines using technologies such as Tekton GitHub Actions and Google Cloud Build.
• Integrate security scanning and other security controls into software development and deployment pipelines.
• Troubleshoot debug and optimize applications to improve performance scalability security reliability and maintainability.
• Use AI-assisted development tools to improve engineering productivity and code quality while following organizational security and responsible-use standards.
• Evaluate and prototype relevant emerging technologies across AI cloud-native engineering DevSecOps and cybersecurity.
• Develop and maintain technical documentation including solution designs API documentation deployment guidance and operational runbooks.
• Apply Agile development practices including sprint planning daily stand-ups backlog refinement and retrospectives.
• Demonstrate curiosity and continuous learning by evaluating new tools frameworks engineering practices and opportunities to apply AI to security and software engineering challenges.

• Bachelors degree in Computer Science Software Engineering Cybersecurity or a related field or an equivalent combination of education training and relevant professional experience.
• Minimum of 4 years of full-stack software engineering experience preferably developing cloud-native applications security products developer platforms or DevSecOps solutions.
• Proficiency in modern front-end technologies such as Angular React and TypeScript with hands-on experience in one or more back-end technologies such as Java/Spring Boot or Python.
• Experience designing and developing APIs web services and data-driven applications.
• Experience with relational or cloud-based data technologies such as PostgreSQL and Google BigQuery.
• Hands-on experience with CI/CD and DevOps technologies such as GitHub GitHub Actions Tekton Google Cloud Build Docker Artifactory and Terraform or comparable technologies.
• Experience with a major cloud platform. Experience with Google Cloud Platform (GCP) services such as Cloud Run Google Kubernetes Engine (GKE) and BigQuery is preferred; relevant experience with Microsoft Azure or Amazon Web Services (AWS) is also applicable.
• Understanding of secure software development practices including secure coding vulnerability management application security and integrating security scanning into CI/CD workflows.
• Familiarity with infrastructure as code (IaC) containerization and cloud-native application delivery.
• Excellent verbal and written communication skills with the ability to explain technical concepts to different audiences and collaborate across security product and engineering teams.

• Experience developing security products security automation or self-service security platforms.
• Experience applying AI/ML large language models (LLMs) or AI-enabled APIs to software engineering or cybersecurity use cases.
• Experience with vulnerability management vulnerability prioritization risk scoring or anomaly detection.
• Working knowledge of Zero Trust architecture and DevSecOps principles.
• Experience with Kubernetes or managed Kubernetes platforms such as GKE.
• Familiarity with AI-assisted development tools and modern software engineering productivity tools.

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