Info Security Architect - AI

• Sep 11, 2026
• Webster, MA, US
• Develop secure-by-design architecture guidelines for AI/ML platforms, including data ingestion, model training, model deployment, and inference layers.
• Define security architectures and guardrails for Generative AI, Agentic AI, AI agents, tool use, orchestration frameworks, and enterprise AI integrations
• Define reference security architectures, patterns, and guardrails that enable secure AI development while minimizing manual review and approval friction.
• Partner with respective engineering teams to automate / integrate in the security guardrails and controls where possible.
• Design risk-based, proportionate AI security controls that satisfy regulatory and enterprise requirements while enabling rapid AI development and experimentation.
• Identify threats unique to AI systems—model inversion, poisoning, evasion attacks, data leakage, prompt injection, etc. Evaluate emerging AI security threats, tools, and best practices.
• Lead AI-specific risk assessments and security design reviews.
• Work with red teams to validate model robustness against adversarial attacks.
• Partner with Data & AI Governance, Advance Analytics, platform engineering, cloud security, and compliance teams.
• Assess the cybersecurity risks associated with third-party AI vendors, models, platforms, and services, and recommend security requirements and mitigating controls.
• Define security logging, monitoring, .detection, and response requirements for AI systems, including agent misuse, prompt attacks, unauthorized model access, abnormal inference activity, and sensitive data exposure.
• Required Skills & Qualifications
• 10+ years in cybersecurity architecture or engineering roles.
• Experience securing enterprise AI platforms and cloud AI services (e.g., Azure OpenAI, AWS Bedrock, Google Vertex AI, Databricks, or equivalent).
• Experience applying AI security and governance frameworks such as NIST AI RMF, MITRE Atlas or similar frameworks.
• Understanding of AI based attacks and threats.
• Strong knowledge of data protection and controls required to protect data.
• Knowledge of creating and communicating cybersecurity risks both in technical and non-technical manner.
• Experience working in AI/ML or data engineering environments.
• Proven track record designing enterprise security frameworks or architecture patterns.
• Excellent communication with technical and non-technical stakeholders.
• Strong analytical, problem-solving, and decision-making abilities.

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