Application Security Engineer

xAI is a technology-driven company focused on creating AI systems that understand the universe and aid humanity. They are seeking a skilled and innovative Application Security Engineer to ensure the security and integrity of their cloud-native applications and systems throughout the software development lifecycle, particularly focusing on code security and CI/CD pipelines.

Responsibilities:

• Conduct in-depth code reviews and static analysis to identify and mitigate security vulnerabilities in our applications
• Design and implement secure coding guidelines and best practices for development teams
• Collaborate closely with development teams to integrate security practices throughout the CI/CD pipeline
• Perform threat modeling and risk assessments for applications, developing mitigation strategies for potential risks
• Manage vulnerability tracking and remediation efforts, providing guidance to development teams
• Support incident response activities related to application security
• Stay current on emerging security threats and trends in cloud-native technologies and AI, continuously enhancing our security measures
• Evaluate and secure software supply chains, including producing and maintaining Software Bills of Materials (SBOMs)
• Address security concerns specific to AI and machine learning models, with a focus on the OWASP LLM Top 10

Requirements:

• Bachelor's degree in Computer Science, Cybersecurity, or a related field
• 3-5 years of experience in application security, with a strong focus on code security practices
• Deep understanding of secure coding practices, application security frameworks, and common vulnerabilities (e.g., OWASP Top 10)
• Proficiency in Python or Rust programming languages and experience with secure coding practices in these languages
• Experience securing CI/CD pipelines and implementing DevSecOps practices
• Familiarity with software supply chain security and SBOM generation tools
• Experience with security testing tools (e.g., Burp Suite, OWASP ZAP) and static/dynamic code analysis
• Understanding of AI/ML security implications, particularly those outlined in the OWASP LLM Top 10
• Excellent communication skills, able to explain complex security issues to both technical and non-technical audiences
• Experience with cloud platforms (e.g., GCP, AWS, Azure) and their security features
• Relevant security certifications (e.g., CSSLP, OSWE)
• Background in data privacy and compliance regulations relevant to cloud-native applications and AI systems
• Experience with GitOps and infrastructure-as-code security
• Familiarity with federated learning and privacy-preserving machine learning techniques
• Experience in building custom security tooling to enhance and automate security processes
• Interest in leveraging AI to automate security tasks and improve efficiency
• Contributions to open-source security projects or tools
• Experience in securing AI/ML models and data pipelines