Want to know if this job is worth applying to?
Bengaluru, Karnataka, India
Onsite
Not Available
This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Cloud Security Validation Engineer based in India.
Join an innovative cloud security engineering environment where you will help validate and strengthen the security of modern cloud infrastructure and runtime environments. In this role, you will design automated testing frameworks and ensure that advanced security features perform reliably across major cloud platforms, including AWS, Azure, and GCP. You will work with Python, eBPF, Linux kernel technologies, containers, and Kubernetes to test security capabilities and identify complex technical issues. Collaborating closely with software and kernel engineers, you will investigate runtime behaviour, reproduce challenging issues, and improve the quality and reliability of security solutions. You will also contribute to continuous integration pipelines that enable faster, more consistent validation of new features. This opportunity is ideal for a technically curious engineer who enjoys automation, cloud-native technologies, and solving complex security challenges in a fast-evolving engineering environment.
Cloud security validation: Design, implement, and maintain automated validation strategies for cloud security features and runtime protection capabilities. Ensure that security functionality performs as expected across different cloud environments and deployment configurations.
Python test automation: Develop and maintain Python-based testing frameworks using tools such as pytest. Create reusable test cases, validate REST APIs, process JSON and YAML configurations, and automate repetitive validation tasks to improve test coverage and efficiency.
eBPF and runtime observability testing: Build and maintain test hooks and validation frameworks for eBPF-based capabilities. Work with kernel-level observability mechanisms to verify runtime security functionality and help ensure accurate detection of relevant system and application behaviour.
Multi-cloud environment management: Configure, deploy, and test security sensors and agents across AWS, Azure, and Google Cloud Platform (GCP). Validate feature behaviour under different infrastructure configurations and investigate platform-specific issues.
Linux kernel investigation: Collaborate with kernel engineers to reproduce, investigate, and debug runtime security issues. Analyse relevant Linux kernel behaviour, system calls, namespaces, and control groups to identify root causes and support effective fixes.
Continuous integration and automated pipelines: Integrate automated security validation into CI/CD workflows using Jenkins, GitHub Actions, or GitLab CI. Improve test execution reliability, provide timely feedback on code changes, and help detect regressions early in the development lifecycle.
Container and Kubernetes testing: Validate security functionality across Docker containers, Kubernetes clusters, pods, and related cloud-native environments. Investigate issues involving container isolation, runtime behaviour, and infrastructure configuration.
Infrastructure automation and observability: Use tools such as Terraform to provision and manage test environments. Leverage monitoring and visualisation tools such as Grafana to support troubleshooting, test analysis, and performance investigation.
Serverless container validation: Test security capabilities in serverless container environments, including AWS Fargate and Google Cloud Run, ensuring consistent behaviour across different deployment models.
Cross-functional engineering collaboration: Work closely with security, platform, and kernel engineering teams to understand technical requirements, improve test coverage, investigate defects, and strengthen the quality and reliability of cloud security features.
Continuous improvement: Identify gaps in existing validation processes, improve test frameworks and automation practices, and contribute to the ongoing evolution of cloud security testing methodologies and engineering standards.
Cloud engineering experience: Hands-on experience configuring and working with at least one major cloud platform, with practical familiarity across AWS, Azure, and GCP. The ability to deploy infrastructure, configure cloud services, and troubleshoot cloud-based environments is important.
Python automation expertise: Strong Python programming and test automation skills, including experience with pytest, REST API testing, and structured data formats such as JSON and YAML. You should be able to develop maintainable automation frameworks and reusable validation components.
Linux internals: Familiarity with Linux kernel concepts, including system calls, namespaces, control groups (cgroups), and kernel modules. The ability to investigate low-level system behaviour and troubleshoot runtime issues is highly valuable.
eBPF knowledge: Experience with eBPF technologies and kernel-level observability is highly desirable. An understanding of how eBPF-based instrumentation operates and how to validate its behaviour will be a strong advantage.
Containerisation and orchestration: Hands-on experience with Docker, containers, Kubernetes, and pods. You should understand containerised application environments and be comfortable testing security functionality across cloud-native deployments.
Infrastructure as code and monitoring: Practical familiarity with Terraform for infrastructure provisioning and Grafana for monitoring and visualisation. Experience creating repeatable test environments and analysing system behaviour is beneficial.
CI/CD and test integration: Experience integrating automated tests into continuous integration and delivery pipelines using Jenkins, GitHub Actions, GitLab CI, or comparable tools. Understanding test automation, regression detection, and pipeline reliability is important.
Serverless technologies: Exposure to serverless container platforms such as AWS Fargate and Google Cloud Run is an advantage, particularly when validating security behaviour across different execution environments.
Analytical and debugging skills: Strong problem-solving abilities, attention to detail, and a structured approach to investigating complex technical issues. You should be able to reproduce failures, identify potential root causes, and collaborate with engineers to validate fixes.
Communication and teamwork: Ability to work effectively with multidisciplinary engineering teams, explain technical findings clearly, document test results, and contribute to continuous improvement initiatives.
Engineering mindset: A proactive, quality-focused approach to software validation, with an interest in cloud security, runtime protection, automation, and emerging infrastructure technologies.
Full-time employment opportunity based in India.
Opportunity to work on advanced cloud security and runtime protection technologies.
Exposure to major cloud platforms, including AWS, Azure, and GCP.
Hands-on experience with modern technologies such as Python, eBPF, Linux kernel internals, Kubernetes, Docker, and infrastructure automation.
Opportunity to collaborate with experienced security, platform, and kernel engineers on complex technical challenges.
Scope to influence automated testing frameworks, validation strategies, and the reliability of security products.
Exposure to cloud-native, containerised, and serverless infrastructure environments.
Opportunities to deepen technical expertise in cloud security engineering, runtime observability, and test automation.