AI Security Architect

BNY Mellon • Pittsburgh, PA

6h • $142,000 - $259,000

About The Position

BNY is seeking a AI Security Architect to lead the design, implementation, and governance of security controls for AI/ML systems across the enterprise. This role will define the target architecture and security patterns for AI-enabled products and platforms, ensuring resilient, compliant, and trustworthy AI. The ideal candidate combines deep expertise in cybersecurity and cloud with hands-on knowledge of modern AI/ML infrastructure, data protection, adversarial threat models, and secure MLOps.

Requirements

• 12+ years in cybersecurity/enterprise security architecture with 3+ years focused on AI/ML or data platform security at scale.
• Expertise in cloud security (AWS/Azure/GCP) including identity, secrets management, key management (KMS/HSM), network segmentation, and policy-as-code.
• Strong knowledge of AI/ML workflows: data ingestion/feature engineering, model training/inference, MLOps tooling (model registry, orchestrators, serving).
• Practical experience with adversarial ML concepts and defenses; familiarity with model robustness, prompt injection risks, and secure evaluation methods.
• Proficiency in designing observability/telemetry for AI systems (e.g., logging prompts/outputs, drift/quality metrics, safety events) with SIEM/SOAR integration.
• Hands-on with infrastructure-as-code (Terraform/CloudFormation), CI/CD, and secure SDLC practices tailored to data/ML systems.
• Deep understanding of data protection (encryption, tokenization, anonymization), privacy by design, and secure data lifecycle management.
• Strong stakeholder management and communication skills; ability to convert complex risks into clear architecture decisions and implementation guidance.

Nice To Haves

• Experience architecting secure AI agents and LLM applications including guardrails, content filters, and output validation.
• Familiarity with standards and frameworks relevant to AI and data (e.g., NIST AI RMF, cloud CIS benchmarks, OWASP for ML/LLM, privacy controls).
• Background in model governance and risk management (e.g., testing for drift, bias, stability, and explainability) and integration with enterprise control frameworks.
• Programming/scripting proficiency (Python preferred) for reference implementations, automation, and security tooling integrations.
• Experience with container security, Kubernetes, service mesh, and microservices patterns in AI platforms.
• Prior leadership in enterprise-scale transformations, enabling secure adoption of AI across multiple business lines.

Responsibilities

• Define enterprise AI security architecture: develop reference architectures, guardrails, and standards for secure data pipelines, model training/inference, and AI-integrated applications across on-prem and cloud.
• Secure MLOps/ML platforms: architect identity, secrets management, network segmentation, and least-privilege access for feature stores, model registries, orchestration, and deployment pipelines.
• Data protection by design: establish controls for sensitive data ingestion, anonymization/pseudonymization, encryption (at rest/in transit), tokenization, and lineage across AI workflows.
• Adversarial ML defense: design controls and tests for model poisoning, evasion, model theft/exfiltration, prompt injection, jailbreaking, data leakage, and output manipulation.
• AI supply chain security: govern third-party models, APIs, and datasets; enforce SBOMs for AI components; evaluate provenance, licensing, and dependency risk.
• Policy and governance integration: translate AI security requirements into actionable standards and control evidence; align with enterprise risk, compliance, and model governance processes.
• Threat modeling and security testing: lead threat modeling for AI systems; design red-teaming and secure evaluation methods for models and agents; integrate chaos/resilience testing.
• Secure development lifecycle: embed AI-specific security checks (static/dynamic scans, IaC policy-as-code, data quality gates, bias/robustness checks) into CI/CD and change management.
• Runtime protection: implementing guardrails, content filters, output validation, rate limiting, anomaly detection, and monitoring for AI services and agentic workflows.
• Observability and incident response: define logging/telemetry (model inputs/outputs, drift, performance, safety events); integrate AI-specific playbooks into SOC operations.
• Zero Trust for AI: design identity-aware access, micro-segmentation, and continuous verification for data scientists, services, and agents.
• Privacy and ethics controls: partner with privacy and legal to operationalize consent, minimization, purpose limitation, and responsible AI guardrails, including human-in-the-loop where appropriate.
• Resilience and continuity: design disaster recovery, backup/restore, model reproducibility, and contingency plans for AI platforms and critical use cases.
• Vendor/platform assessments: evaluate cloud AI services, open-source frameworks, and commercial tools for security posture, compliance, and fit-for-purpose.
• Risk management: lead control testing and risk assessments for AI initiatives; document residual risks and remediation plans; support audits and regulatory queries.
• Reference implementations: deliver secure patterns, sample code, and automation (e.g., reusable Terraform/Policy-as-Code, secrets patterns, logging schemas) to accelerate adoption.
• Stakeholder leadership: partner with platform engineering, data science, enterprise architecture, cyber operations, and product teams to drive end-to-end secure outcomes.
• Coaching and enablement: build education and guidance for architects, data scientists, and engineers on secure AI practices, design patterns, and common pitfalls.
• Continuous improvement: track emerging threats, standards, and best practices; lead updates to architecture and controls; measure effectiveness via KPIs and control health.

Benefits

• BNY offers highly competitive compensation, benefits, and wellbeing programs rooted in a strong culture of excellence and our pay-for-performance philosophy.
• We provide access to flexible global resources and tools for your life’s journey.
• Focus on your health, foster your personal resilience, and reach your financial goals as a valued member of our team, along with generous paid leaves, including paid volunteer time, that can support you and your family through moments that matter.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees