AI Security Architect

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Job Description

Job Title : Cloud Security Architect with AI
Type : FTE ( No Subcontractor or C2C)
Mode : Hybrid
Location : Atlanta /Dallas/Chicago
Visa : No Sponsorship Available

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About the Role:

We are seeking an experienced AI Security Architect to support the secure design, development, and deployment of AI/ML and Generative AI solutions across the enterprise. This role will work closely with data science and engineering teams, product owners, cloud/platform teams, and the security architecture and operations groups to define and implement security requirements that enable compliant, resilient, and trustworthy AI adoption.

Key Responsibilities:

Collaborate with AI/ML engineering, data engineering, platform, and application teams to gather and analyze AI security requirements (data sourcing, model training, inference, integrations, and operational workflows).
Define and document secure reference architectures for AI/ML and GenAI workloads across cloud and enterprise environments, including patterns for model hosting, RAG, agents, API exposure, and third-party model consumption.
Perform threat modeling for AI systems (training and inference) including risks such as prompt injection, data leakage, model inversion/extraction, insecure plugins/tools, and supply chain risks.
Establish security controls for data protection across the AI lifecycle: dataset governance, data minimization, labeling/classification alignment, encryption, key management, secrets handling, and secure data access patterns.
Define requirements and guardrails for GenAI safety and misuse prevention, including content filtering, prompt/response logging strategy, abuse detection, and safe tool execution.
Partner with IAM teams to implement least-privilege access for AI platforms, model endpoints, feature stores/vector databases, and supporting pipelines (service-to-service auth, token handling, RBAC/ABAC).
Review and approve AI solution designs, ensuring alignment with security policies, regulatory expectations, and enterprise standards (secure SDLC/DevSecOps).
Define requirements for model governance and assurance (model provenance, versioning, artifact integrity, evaluation/validation controls, documentation, and auditability).
Work with security operations to integrate AI platforms into monitoring and incident response, including logging requirements, detection use cases, and response playbooks for AI-specific incidents.
Contribute to security standards and best practices: “when to use enterprise controls vs platform-native controls,” secure configuration baselines, and reusable implementation guidance.
Required Qualifications:

5+ years of experience in security architecture/engineering, with demonstrated experience securing cloud-native applications and APIs (AI/ML experience required).
Strong understanding of AI/ML and GenAI solution patterns (model training vs inference, RAG, vector databases, agents/tool use, model endpoints).
Proven ability to translate business and technical requirements into actionable security controls and architecture decisions.
Experience with cloud security fundamentals (network segmentation, IAM, encryption, secrets management, logging/monitoring) in at least one major cloud provider (AWS/Azure/GCP).
Hands-on experience with application security and API security (authN/authZ, OWASP Top 10, secure SDLC, threat modeling).
Familiarity with AI/ML security risks and mitigations (prompt injection, data leakage, jailbreaks, model theft, poisoning, insecure dependencies).
Strong communication skills—able to document and present complex technical topics to engineering and leadership audiences.
Ability to work independently and drive results in a fast-paced, multi-team environment.

Job Description - Grade Specific

Is highly respected, experienced and trusted. Masters all phases of the software development lifecycle and applies innovation and industrialization. Shows a clear dedication and commitment to business objectives and responsibilities and to the group as a whole. Operates with no supervision in highly complex environments and takes responsibility for a substantial aspect of Capgeminis activity. Is able to manage difficult and complex situations calmly and professionally. Considers ˜the bigger picture when making decisions and demonstrates a clear understanding of commercial and negotiating principles in less easy situations. Focuses on dev