Lead AI Security Engineer

Description

The ideal candidate combines offensive and defensive security expertise with strong experience in secure system design, cloud infrastructure, CI/CD, containers, and modern software delivery pipelines. They will help define and execute new AI security initiatives across the enterprise, especially in a regulated financial services environment where confidentiality, resilience, governance, and auditability are critical.

Essential Job Functions

• Lead security initiatives for LLM-powered applications, copilots, agentic systems, and AI-assisted workflows.
• Design and implement controls to reduce the risks of prompt injection, sensitive information disclosure / data leakage, improper output handling, excessive agent autonomy, model and AI supply chain risk, vector / embedding and retrieval-related weaknesses.
• Partner with engineering teams to embed secure-by-design patterns into AI application development, deployment, and operations.
• Create guardrails for AI systems that process customers, employees, and regulate financial data.
• Architect and implement AI gateway controls that centralize security policy enforcement for model traffic, including prompt inspection, response filtering, PII/secret redaction, model access control, rate limiting / abuse prevention, audit logging and evidence generation.
• Define runtime security policies for AI interactions across internal applications, APIs, tools, and model providers.
• Build detection and response capabilities for malicious prompts, unsafe model behavior, and data exfiltration attempts.
• Secure systems built on the Model Context Protocol (MCP) and related AI tool-integration patterns.
• Define security requirements for MCP servers, proxy servers, and tool connectors, including authentication and authorization, least privilege, schema/input validation, secrets management, network isolation, sandboxing, logging and auditability, third-party server risk review.
• Assess and mitigate risks associated with MCP architecture, including authorization flaws, confused-deputy scenarios, and unsafe execution paths.
• Partner with Cloud Security, Platform Engineering, and DevOps to implement hardening, segmentation, identity controls, observability, and incident response readiness.
• Work closely with Security, Engineering, Legal, Compliance, Risk, and Product teams to align AI security controls with regulatory and internal risk expectations.
• Help define AI security standards, reference architectures, guardrails, and review processes appropriate for a financial industry environment.

Position Requirements

• 5+ years of experience in cybersecurity with a strong mix of offensive and defensive security tactics.
• Deep familiarity with the OWASP Top 10 for LLM Applications.
• Hands-on experience with Docker, Kubernetes, and Cloud Security (AWS/Azure/GCP).
• Experience designing and securing AI gateways, API proxies, or centralized policy enforcement layers for AI workloads.
• Working knowledge of MCP server security and secure tool-integration patterns, including identity, authorization, validation, proxy risks, and logging.
• Strong communication skills with the ability to work across Application Security, Cloud Infrastructure, Platform Engineering, and Product Engineering teams.
• Familiarity with AI red teaming methodologies and adversarial testing for LLM applications.
• Able to translate complex AI risks into actionable technical requirements for developers and executive stakeholders.
• Familiarity with regulatory frameworks (e.g., NIST AI RMF, ISO/IEC 42001).

About the Role

We are seeking an experienced AI Security Engineer to lead the design, implementation, and operationalization of security controls for our LLM-powered applications, AI platforms, and model-hosting infrastructure. This role will focus on protecting AI systems from prompt injection, sensitive data leakage, insecure tool use, model abuse, and cloud/infrastructure threats, while helping establish secure engineering patterns for the next generation of AI-enabled products.

Skills

• Experience with LLM Applications
• Experience with Docker, Kubernetes, and Cloud Security (AWS/Azure/GCP)
• Experience with AI gateways, API proxies, or centralized policy enforcement layers for AI workloads
• Experience with MCP server security and secure tool-integration patterns
• Experience with OWASP Top 10 for LLM Applications
• Experience with AI red teaming methodologies and adversarial testing
• Experience with regulatory frameworks (e.g., NIST AI RMF, ISO/IEC 42001)

Benefits

At Credit One Bank, we offer a competitive benefits package that includes:

• Health insurance
• Dental insurance
• Vision insurance
• Paid time off
• Flexible spending accounts
• Retirement savings plans
• Employee assistance programs
• Professional development opportunities

Pay

Salary range: $120,000 - $160,000 per year

Schedule

Full-time, Monday-Friday, 8:00 AM - 5:00 PM