AI Security Engineer

About this role

Requirements

• Deep expertise in application security, AI/ML risk, and cloud-native security engineering.
• Subject matter expert in AI security with proven experience as a trusted partner to Engineering, Product, DevSecOps, Legal/Privacy, and Security Operations.
• Proficiency in threat modeling for generative AI systems, including prompt injection, data poisoning, model extraction, model inversion, and data leakage.
• Knowledge of OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF frameworks.
• Experience implementing security controls across the AI/ML lifecycle (data ingestion, training, evaluation, deployment, monitoring).
• Ability to define and operationalize AI-specific monitoring, detection, and incident response capabilities integrated with SIEM/SOC workflows.
• Strong cross-functional collaboration skills and ability to balance risk reduction with business velocity.

Responsibilities

• Leads AI Security Architecture & Secure Design initiatives, implementing lifecycle security controls across data ingestion, training, evaluation, deployment, and monitoring environments to measurably reduce AI-specific risk while maintaining product velocity.
• Conducts structured Threat Modeling & Risk Assessment for generative AI, RAG, and agent-based systems, evaluating risks such as prompt injection, data poisoning, model extraction, and data leakage, and mapping findings to OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI RMF.
• Defines and operationalizes Monitoring, Detection & Incident Response capabilities for AI systems by implementing prompt and output telemetry, tool-call logging, anomaly detection, and AI-specific incident response playbooks integrated into SIEM/SOC workflows.
• Delivers measurable outcomes aligned to 30-, 150-, and 210-day milestones, including secure reference architectures, hardened AI environments, integrated security controls, and executive-ready reporting on AI risk reduction and posture maturity.
• Establishes AI Governance, Privacy & Third-Party Risk requirements, defining security expectations for AI use cases, third-party models, vendor integrations, and sensitive data usage, embedding controls into SDLC, procurement, and engineering standards.
• Drives Cross-Functional Collaboration & Enablement by partnering with Engineering, Data Science, DevSecOps, Product, Legal/Privacy, and SOC teams to align on risk appetite, escalation paths, and secure design guardrails while raising AI security maturity.
• Inventories current and planned AI/ML initiatives, documents system architectures and sensitive-data touchpoints, and implements a structured AI security intake and risk-rating process.

Benefits

• Recognition as a top workplace by USA TODAY and Boston Globe in 2025.
• Mission-driven environment focused on reducing digital exclusion and restoring simplicity to essential service payments.
• Opportunity to work in an award-winning fintech company with leadership in AI maturity and responsible innovation.