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Principal AI Security & Privacy Architect

Job in Virginia, St. Louis County, Minnesota, 55792, USA
Listing for: NTT Global Data Centers Americas, Inc.
Full Time position
Listed on 2026-07-16
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), AI Business & Operations, AI Evaluation, Information Security & Data Protection
Salary/Wage Range or Industry Benchmark: 171200 - 244500 USD Yearly USD 171200.00 244500.00 YEAR
Job Description & How to Apply Below

Make an impact at NTT Global Data Centers

NTT Global Data Centers is a global data center provider with over 150 facilities in more than 20 countries. We drive innovation and sustainability through cutting‑edge technology and transformative projects.

Your role at a glance

The Principal AI Security & Privacy Architect owns the security and privacy architecture for AI/ML‑enabled products and enterprise AI platforms. The role partners across the enterprise to embed secure‑by‑design and privacy‑by‑design controls across the AI lifecycle, delivering trustworthy, compliant, audit‑ready AI solutions tailored to specific business needs.

Key

Roles and Responsibilities
  • AI Architectures
    • Train the business on safe AI usage that aligns with privacy and cybersecurity goals.
    • Coordinate with the parent company on AI solutions, vetting strategies, security and privacy governance and guidance.
    • Design solutions for LLM usage and AI‑generated software that can be easily adopted by the business.
    • Analyze and support proposed AI projects company‑wide, serving as the technical reviewer for the AI Center of Excellence.
  • AI Security, Privacy & Governance Architect
    • Define secure‑by‑design and privacy‑by‑design patterns; translate regulatory and policy requirements (GDPR, DPDPA 2023, NIST AI RMF, ISO 42001) into actionable engineering guidance.
    • Lead hands‑on PIA, DPIA and TPRA assessments for AI/ML systems and data platforms, identifying risks including re‑identification, inference attacks, model inversion and consent gaps.
    • Review AI model cards, training data sourcing practices and automated decision‑making workflows to surface privacy, fairness and transparency risks.
    • Serve as a subject‑matter expert on privacy‑by‑design principles for generative AI, LLMs, recommendation systems and other deployed AI tools.
  • Risk Management & Assurance
    • Define AI risk and control frameworks aligned to the enterprise risk model; drive mitigations, documentation standards and risk acceptance packages.
    • Support the risk register and compliance calendar for AI security and privacy activities, tracking open issues, remediation actions and regulatory deadlines.
    • Prepare and present governance status reports, risk summaries and architectural decision records to senior leadership and relevant committees.
    • Support vendor and third‑party AI tool assessments, including contractual data processing reviews, security questionnaires and due diligence activities.
  • Project Management & Cross‑Functional Leadership
    • Lead end‑to‑end governance and architecture projects — from scoping and stakeholder alignment through implementation and post‑deployment review — on time and within defined parameters.
    • Integrate AI security and privacy requirements into the secure SDLC, architecture review boards, go‑to‑market readiness gates and customer/regulatory assurance responses.
    • Coordinate with Engineering, Data Science, Legal, Product and Compliance teams to embed governance checkpoints throughout the AI/ML development lifecycle.
    • Manage project plans, milestone tracking and status reporting using Jira, Asana or MS Project; proactively surface blockers and drive resolutions across work streams.
    • Facilitate architecture and risk review sessions, documenting decisions and ensuring follow‑through on action items with accountable owners and defined timelines.
Knowledge & Attributes
  • Deep analytical and regulatory interpretation skills to translate complex AI risk requirements into practical guidance.
  • Working knowledge of AI/ML concepts: supervised and unsupervised learning, generative AI, LLMs, automated decision‑making and model governance.
  • Structured, methodical approach to project management – experienced with agile and waterfall delivery frameworks, comfortable with ambiguity, and adept at prioritizing competing demands.
  • Excellent written and verbal communication skills; able to present complex security and risk topics credibly to both technical and executive audiences.
  • Collaborative, curious and proactive – a self‑starter who builds trust with cross‑functional peers and drives initiatives through to measurable outcomes.
Academic Qualifications & Certifications
  • Required:

    Bachelor’s degree – preferably in…
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