About this role

The Full Stack DevSecOps Engineer is responsible for designing, engineering, and delivering security products and platforms from concept through production. The role develops end-to-end solutions spanning front-end applications, back-end services, application programming interfaces (APIs), data pipelines, databases, and cloud infrastructure. The engineer will apply AI and machine learning (AI/ML), where appropriate, to create intelligent automation for security use cases such as vulnerability triage, risk scoring, anomaly detection, and self-service security workflows. The role also embeds secure development practices, Zero Trust principles, and DevSecOps controls throughout the software development lifecycle (SDLC). Working closely with security, product delivery, DevSecOps, and platform engineering teams, this individual will translate security needs and product roadmaps into scalable, reliable, and maintainable engineering solutions.

Required

- Bachelor’s 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.

Preferred

- 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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