Cloud Security​/AI Security Engineer | AWS IAM & Cedar Policies | Remote

• Contract

Location:
Los Angeles, CA
(Remote – 10% Travel; must be comfortable traveling to client sites for workshops and meetings)

Duration: 3+ Months (Extension Possible)

Primary

Skills:

IAM Policy Templates, Cedar Policies

Seeking an experienced Security Engineer with 15+ years of experience in cloud security and identity management to secure enterprise AI applications on AWS. The role focuses on authentication, reusable IAM policy templates, Cedar-based authorization, and secure access to tools, APIs, and enterprise resources.

• Design, develop, and maintain reusable AWS IAM policy templates for AI agents and Agent Core infrastructure.
• Implement role-based access control (RBAC) and least-privilege security principles.
• Define IAM roles, trust policies, permission boundaries, and resource-based policies.
• Configure IAM execution roles for Agent Core Runtime and Agent Core Gateway.
• Develop standardized IAM templates for accessing AWS services such as Lambda, S3, Bedrock, API Gateway, Secrets Manager, and Cloud Watch.
• Automate IAM policy deployment and configuration using Terraform, AWS Cloud Formation, or AWS CDK.
• Conduct IAM access reviews, permission audits, and policy validation.
• Troubleshoot access-denied issues, role-assumption failures, and authorization misconfigurations.

• Design, author, test, and deploy Cedar authorization policies using Amazon Bedrock Agent Core Policy.
• Implement fine-grained authorization for AI agents accessing tools through Agent Core Gateway.
• Define policies specifying which identities can invoke particular tools, APIs, and operations.
• Configure policy engines and associate them with Agent Core Gateways.
• Implement attribute-based access control (ABAC) using identity attributes, roles, scopes, and contextual conditions.
• Develop policies that restrict sensitive tool operations based on business roles, permissions, and security requirements.
• Validate Cedar policies against gateway schemas and test permitted and denied access scenarios.
• Enforce default-deny authorization and prevent unauthorized tool execution.
• Monitor and troubleshoot authorization decisions and policy evaluation failures.

• Implement security controls for enterprise AI agents and Generative AI applications.
• Develop security standards for agent identities, API integrations, and access management.
• Support audit logging, access traceability, and security monitoring using AWS Cloud Trail and Cloud Watch.
• Identify and mitigate risks including excessive privileges, credential exposure, unauthorized tool access, and privilege escalation.
• Conduct security reviews of agent architecture and integrations.
• Collaborate with AI engineering and Dev Ops teams to ensure secure production deployments.

• Automate security policy deployment through Git Hub Actions and infrastructure-as-code pipelines.
• Integrate IAM and Cedar policy validation into CI/CD workflows.
• Implement automated security checks and policy compliance testing.
• Maintain version-controlled security configurations across development, testing, and production environments.
• Support security incident investigation, access troubleshooting, and remediation.

• AWS Security: IAM, IAM roles, policies, STS, AWS Secrets Manager, Cloud Trail, Cloud Watch.
• Authorization: Cedar policy language, RBAC, ABAC, fine-grained access control.
• Infrastructure as Code: Terraform, AWS CDK, or Cloud Formation.
• Automation: Python, Git Hub Actions, CI/CD security integration.
• Cloud Security: Least-privilege access, identity federation, credential management, and secure API integrations.

All your information will be kept confidential according to EEO guidelines.