Staff Security Engineer - Cloud & AI Security
Xerox
- Location
- Remote (India)
- Employment
- Full-time
- Level
- Senior Level
About the Role
Xerox is seeking a Staff Security Engineer to design and implement security architectures for AI and machine learning workloads across AWS and Azure. This role focuses on securing generative and agentic AI applications through threat modeling, vulnerability management, and incident response.
Skills
Perks
- Remote Work
Full job details
General Information
Description & Requirements
For more than 100 years, Xerox has continually redefined the workplace experience. Harnessing our leadership position in office and production print technology, we’ve expanded into software and services to sustainably power the hybrid workplace of today and tomorrow. Today, Xerox is continuing its legacy of innovation to deliver client-centric and digitally-driven technology solutions and meet the needs of today’s global, distributed workforce. From the office to industrial environments, our differentiated business and technology offerings and financial services are essential workplace technology solutions that drive success for our clients. At Xerox, we make work, work. Learn more about us at www.xerox.com.
Overview:
Xerox is seeking a Senior AI Security Engineer to help secure AI and machine learning technologies across AWS and Microsoft Azure cloud environments. This role will design and implement security solutions for AI powered applications, including generative and agentic AI implementations. You will collaborate with Data Science, DevOps, and Engineering teams to integrate security throughout the AI and ML lifecycle while helping Xerox address evolving security threats and requirements.
Why Join This Team:
• Help shape security practices for AI, machine learning, generative AI, and agentic AI solutions.
• Work across AWS, AWS Bedrock, and Microsoft Azure cloud environments.
• Collaborate with Data Science, DevOps, Engineering, and other cross functional teams.
• Apply established AI security frameworks to evaluate risks and strengthen AI solutions.
• Work model is remote. Benefits and compensation details to be confirmed.
What You Will Do:
• Conduct security risk assessments, threat modeling, and vulnerability management for cloud based AI and ML workloads, including adversarial and generative AI attack scenarios.
• Design and manage security architectures, policies, and controls for AI and ML services across AWS, AWS Bedrock, and Microsoft Azure.
• Develop safeguards for AI data, models, endpoints, APIs, MCP servers, prompts, and LLM implementations, including access controls, encryption, and network security.
• Collaborate across teams to integrate security throughout the AI and ML lifecycle and monitor, respond to, mitigate, and remediate security incidents.
• Apply AWS Bedrock security practices and stay current with emerging AI and ML threats, vulnerabilities, security frameworks, and regulatory requirements.
What You Need to Succeed:
• Bachelor's degree or equivalent practical experience, with at least 10 years of experience in security assessments, security design reviews, or threat modeling.
• At least 4 years of experience in cloud security, security engineering, computer security, or network security, including at least 2 years focused on AI and ML technologies in cloud environments.
• Hands on experience with Microsoft Azure AI and AWS, including AWS Bedrock, and designing cloud security controls such as IAM, KMS, VPC, encryption, and network segmentation.
• Knowledge of AI and ML security risks and adversarial techniques, including prompt injection, jailbreak testing, evasion, poisoning, model inversion and extraction, secure prompt engineering, LLM guardrails, and responsible AI practices.
• Ability to assess AI security risks using frameworks such as AI RMF, OWASP ML Security Top 10, and MITRE ATLAS, combined with effective analytical, problem solving, stakeholder management, and communication skills.
How We Set You Up for Success:
• Provide opportunities to work across cloud based AI and ML technologies and evolving AI security challenges.
• Enable close collaboration with Data Science, DevOps, Engineering, and other cross functional teams.
• Support the application of security automation and infrastructure as code practices, including Terraform and CloudFormation.
• Provide opportunities to apply and expand knowledge of secure AI deployment, adversarial robustness, and responsible AI practices.
• Value relevant professional certifications, including AWS Certified Security Specialty and CISSP, as preferred qualifications.