JJobsSonar

Lead AI Security Architect 2026 - US (Remote)

ChatGPT Jobs · Atlanta, GA

SecurityRemote

About this role

The AI Security Engineer / Architect will apply strategic thinking to help customers securely adopt enterprise AI tools, modernize security architectures, and govern risks from generative AI platforms. Responsibilities include assessing existing security, identity, data, cloud, and SaaS architectures to advise on best-in-class solutions for securing enterprise AI tooling. The role involves designing and implementing security controls for AI platforms, such as SSO, SCIM, RBAC, MFA, conditional access, and audit logging. The individual will also evaluate AI platform features, review and secure AI integrations with enterprise repositories and collaboration platforms, and manage end-to-end AI Security Implementation efforts. The role includes owning client engagements, contributing to AI Security practice development, and aiding business development.

Skills & technologies

Must have

  • AWS
  • Azure
  • GCP
  • SSO
  • SCIM
  • RBAC
  • MFA
  • Conditional Access
  • Admin Roles
  • User Lifecycle Management
  • Retention Policies
  • Audit Logging
  • DLP
  • Acceptable-Use Enforcement
  • Identity Providers
  • Okta
  • Microsoft Entra
  • Google Workspace
  • Microsoft 365
  • Slack
  • Atlassian
  • GitHub
  • GitLab
  • Splunk
  • Sentinel
  • Datadog
  • Python
  • APIs
  • Terraform
  • CI/CD Pipelines
  • GitHub Actions
  • GitLab CI
  • Container Technologies
  • Infrastructure-as-Code
  • Threat Modeling
  • SIEM/SOAR
  • Secure SDLC
  • Application Security Testing
  • API Security
  • Secrets Management

Nice to have

  • OWASP Top 10 for LLM Applications
  • MITRE ATLAS
  • NIST AI RMF
  • ISO 42001
  • SOC 2
  • HIPAA
  • PCI DSS
  • GDPR

Read full description

About the job Job Description Job Title: AI Security Engineer / Architect Location: Atlanta, GA (Remote; local hybrid option at Sandy Springs, GA headquarters) Job Summary Aimpoint Digital is seeking an experienced security engineer/architect to apply strategic thinking for helping customers securely adopt enterprise AI tools, modernize security architectures, and govern risks from generative AI platforms. Responsibilities Assess existing security, identity, data, cloud, and SaaS architectures to advise on best-in-class solutions for securing enterprise AI tooling across industries. Conduct comprehensive evaluations of AI tools (e.g., Claude, Claude Enterprise), including platform configurations, data access patterns, and security controls. Design and implement security controls for enterprise AI platforms, including SSO, SCIM, RBAC, MFA, conditional access, admin roles, user lifecycle management, retention policies, audit logging, workspace controls, DLP, and acceptable-use enforcement. Assess and govern AI platform features such as file uploads, custom assistants, projects, connectors, browsing, code execution, data analysis, plugins, agents, API access, and external sharing. Review and secure AI integrations with enterprise repositories and collaboration platforms (e.g., Google Drive, SharePoint, OneDrive, Slack, Teams, GitHub, GitLab, Jira, Confluence, Salesforce, Snowflake, Databricks, BI platforms). Manage end-to-end AI Security Implementation efforts, including identity integration, access control design, data protection controls, AI platform configurations, connector governance, monitoring/logging, and incident response workflows. Qualifications Baseline Skills (Required): Degree in Computer Science, Cyber Security, Information Systems, Engineering, or equivalent experience. Strong written and verbal communication, especially for C-Suite/executive audiences. Experience designing and delivering enterprise security architectures (cloud, SaaS, data, application, or security operations). Experience securing SaaS platforms using SSO, SCIM, RBAC, MFA, conditional access, logging, DLP, lifecycle management, and administrative controls. Experience with identity providers and collaboration platforms: Okta, Microsoft Entra, Google Workspace, Microsoft 365, Slack, Atlassian, GitHub, GitLab. Experience with cloud platforms: AWS, Azure, GCP. Experience with secure SDLC, application security testing, API security, secrets management, vulnerability management, and software supply chain (must-have). Experience performing threat modeling and translating risk into practical controls. Experience integrating security telemetry into SIEM/SOAR platforms (e.g., Splunk, Sentinel, Datadog). 5+ years experience in security engineering, cloud security, application security, data security, IAM, security architecture, or security operations. 5+ years experience with cloud/enterprise SaaS platforms or modern data platforms (Databricks/Snowflake/Fabric/Big Query). Experience with generative AI platforms, especially Claude Enterprise. Familiarity with LLM security risks (prompt injection, sensitive information disclosure, insecure output handling, excessive agency, retrieval abuse, software supply chain risk). Familiarity with AI security/governance frameworks (OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, ISO 42001, SOC 2, HIPAA, PCI DSS, GDPR) desirable. Experience with Python, APIs, Terraform, CI/CD pipelines, GitHub Actions, GitLab CI, container technologies, or infrastructure-as-code security desirable. Experience conducting AI red teaming, adversarial testing, abuse-case analysis, or model-integrated application security reviews desirable. Advanced cloud certification (AWS, Azure, GCP) desirable. Security certifications (CISSP, CCSP, CISM, GIAC, AWS Security Specialty, Azure Security Engineer, Google Professional Cloud Security Engineer) desirable. Additional Information Fully remote position; Atlanta-based applicants can work in Sandy Springs, GA headquarters. Role includes owning client engagements, contributing to AI Security practice development, and aiding business development. Company: Aimpoint Digital
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