DevSecOps Full Stack Security Engineer

We are seeking a highly skilled DevSecOps Full Stack Security Engineer to join our team in Chennai, Tamil Nadu, India. As a DevSecOps Full Stack Security Engineer, you will be 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. You will apply AI and machine learning (AI/ML) to create intelligent automation for security use cases such as vulnerability triage, risk scoring, anomaly detection, and self-service security workflows.

Responsibilities

• 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 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 organisational 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.

Qualifications

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.