Lead AI Security Architect 2026 - US

Aimpoint Digital • Atlanta, GA

2d • Remote

About The Position

Aimpoint Digital is a fully remote, rapidly growing AI and Data Engineering consultancy. We specialize in enabling tangible business outcomes and ROI for organizations around the globe. AI is fundamentally changing how the world works, and our philosophy toward AI security is a combination of mitigating risk without slowing innovation. What sets us apart is our track record of providing strategic advisory services alongside unmatched delivery expertise. In this position, you will be a crucial member in shaping the future of AI; specifically, by enabling designing scalable security architectures that enable organizations to innovate both quickly, and securely. You will design and implement security solutions that enable customers to securely deploy, and govern, Claude Enterprise.

Requirements

• Degree in Computer Science, Cyber Security, Information Systems, Engineering, or equivalent experience
• Strong written and verbal skills; specifically with respect to C-Suite / Executive communication
• Experience designing and delivering enterprise security architectures (projects or otherwise), particularly across 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 working with identity providers and collaboration platforms like Okta, Microsoft Entra, Google Workspace, Microsoft 365, Slack, Atlassian, GitHub and/or GitLab
• Experience working with Cloud Platforms such as AWS, Azure and/or GCP
• Experience with secure SDLC, application security testing, API security, secrets management, vulnerability management and software supply chain (this is a must-have)
• Experience performing threat modelling and translating risk into practical technical and operational controls
• Experience integrating security telemetry into SIEM/SOAR platforms such as Splunk, Sentinel, Datadog or similar technologies
• 5+ years experience in security engineering, cloud security, application security, data security, IAM, security architecture or security operations
• 5+ years experience working with cloud / enterprise SaaS platforms or modern data platforms (specifically Databricks / Snowflake / Fabric / Big Query)
• Experience with generative AI platforms; Claude Enterprise specifically
• Familiarity with LLM security risks such as prompt injection, sensitive information disclosure, insecure output handling, excessive agency, retrieval abuse and software supply chain risk

Nice To Haves

• Familiarity with AI security and governance frameworks such as OWASP Top 10 for LLM Applications, MITRE ATLAS, NIST AI RMF, ISO 42001, SOC 2, HIPAA, PCI DSS, GDPR, or similar frameworks is desirable
• Experience with Python, APIs, Terraform, CI/CD pipelines, GitHub Actions, GitLab CI, container technologies, or infrastructure-as-code security is desirable
• Experience conducting AI red teaming, adversarial testing, abuse-case analysis, or model-integrated application security reviews is desirable
• Advanced certification in one or more cloud platforms, such as AWS, Azure, or GCP, is desirable
• Security certifications such as CISSP, CCSP, CISM, GIAC, AWS Security Specialty, Azure Security Engineer, Google Professional Cloud Security Engineer, or similar credentials are desirable

Responsibilities

• Assess existing security, identity, data, cloud and SaaS architectures and advise on best-in-class solutions for securing enterprise AI tooling across customers in a wide range of industries
• Conduct comprehensive evaluations of AI tools (e.g. Claude, Claude Enterprise), platform configurations, data access patterns, connector usage, security controls, processes and personnel to deliver informed recommendations leveraging your expertise in security engineering and AI governance
• 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, GPTs, connectors, browsing, code execution, data analysis, plugins, agents, API access, and external sharing
• Review and secure AI integrations with enterprise repositories and collaboration platforms, including Google Drive, SharePoint, OneDrive, Slack, Teams, GitHub, GitLab, Jira, Confluence, Salesforce, Snowflake, Databricks, and BI platforms
• Manage and lead end-to-end AI Security Implementation efforts as part of a project team; including activities such as identity integration, access control design, data protection controls, AI platform configurations, connector governance, monitoring / logging and incident response workflows

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree