Job Summary
The AI Security Automation Engineer is responsible for designing a resilient self healing infrastructure capable of defending against automated high frequency vulnerability discovery Their mission is to bridge the gap between AI driven threat identification and instantaneous architectural response ensuring the organizations defense operates at machine speed
Responsibilities
Integrate and manage frontier AI models and LLMbased security tools to perform continuous autonomous redteaming of production and development environments
Design and maintain automated pipelines that trigger immediate defensive actionssuch as virtual patching microsegmentation or credential rotationupon the discovery of valid exploit paths
Develop infrastructure templates TerraformAnsible that allow for the rapid hardening of the environment in response to newly discovered classes of algorithmic attacks
Analyze how frontier models chain minor vulnerabilities into complex exploits and use those insights to redesign architectural guardrails
Build APIdriven connections between autonomous discovery engines and the broader security stack WAF SIEM and CICD pipelines
Candidate Experience Requirements
58 years in Cybersecurity with at least 3 years in DevSecOps Cloud Security Engineering or Security Automation
Strong background in penetration testing or vulnerability research with a focus on logicbased exploits rather than just signaturebased flaws
Advanced proficiency in Python Go or similar languages specifically for building automated workflows and interacting with LLM APIs
Deep expertise in cloudnative security architectures AWSAzureGCP and container orchestration Kubernetes
- Participate in incident response activities related to cloud based payment systems by providing expert insights into pipeline configurations automation scripts and access controls that may influence containment and recovery steps.
- Optimize security tooling integration within DevSecOps pipelines to balance robust protection with efficient developer experience thereby supporting continuous delivery objectives for payment capabilities.
- Review code and configuration changes associated with cards and payments platforms to validate adherence to secure coding practices encryption requirements and segregation of duties models before production promotion.
Qualifications
- Demonstrate four to eight years of hands on cyber security experience with significant focus on Azure automation capabilities such as runbooks pipelines and policy driven enforcement for complex applications.
- Show proven expertise implementing DevSecOps methodologies including integrating security testing tools secrets management and configuration validation within multi stage CI CD pipelines.
- Exhibit practical experience with AWS DevOps services including code repository build deployment and monitoring components configured to support strong identity management logging and security guardrails.
- Bring solid understanding of security practices tailored to financial services with particular depth in cards and payments operations transaction flows and protection of sensitive account data.
- Display familiarity with industry standards and regulations that influence payment security such as data protection expectations encryption key handling and secure network segmentation principles.
- Apply strong scripting and automation abilities using commonly adopted languages to build reusable secure components that streamline compliance and reduce repetitive operational tasks.
- Communicate clearly with technical and non technical stakeholders to explain security risks tradeoffs and mitigation approaches while working within hybrid teams distributed across multiple locations.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
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