AI Security Engineer Lead

• Location: Charlotte NC - 600 S Tryon St.
• The position is described below. If you want to apply, click the Apply button at the top or bottom of this page. You'll be required to create an account or sign in to an existing one.
• If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response).

Regular or Temporary

Regular

Language Fluency: English (Required)

Work Shift

1st Shift (United States of America)

Please review the following job description

CRC is putting AI agents to work across the business, and we need a hands-on leader to make sure they are built and run securely from day one. The AI Security Engineer Lead owns the engineering of security controls for agentic AI: the agent harnesses that house and orchestrate agents, tools, the MCP servers and APIs that agents call, agent-to-agent (A2A) interactions, and the AI and API gateways that sit in the path. This role designs reusable security patterns, builds and operates the controls that enforce them, and proves those controls actually work.

This is a builder’s role with real influence. The ideal candidate partners closely with AI Innovation, Data Management and Analytics, Enterprise Architecture, and Application and AI Agent Developers to make the secure path the easy path, and communicates risk and progress clearly to both technical and executive stakeholders. Note: CRC is almost-exclusively a Microsoft Azure shop, so the ideal candidate will be able to demonstrate their competence and successes securing AI workloads in Microsoft Foundry and Azure API Management (APIM). Anthropic control experience is also highly-desirable.

Key Responsibilities

AI Security Leadership

• Lead the AI Security function, including development and delivery of AI Security Service Offerings, reference architectures, operational runbooks, and a roadmap for continual improvement.
• Partner with Cybersecurity Architects and Engineers, IT Infrastructure Engineers, and Application and AI Agent Developers to embed security into AI solutions from design through production.
• Partner with Project and Program Management to ensure that we’re executing the right work with the right priorities.
• Partner with GRC to keep AI use compliant with CRC policy and regulatory obligations (including NYDFS, among others), and to remediate any findings or observations.
• Maintain the ability to quickly report on current state, risk posture, and progress maturing this space.

Agent Harness Security Patterns

Develop, publish, and maintain secure design patterns for AI agent harnesses, covering tool permissioning, sandboxing, human-in-the-loop approvals, memory and context handling, and safe failure modes.

Define guardrails against prompt injection (direct and indirect), tool misuse, excessive agency, data leakage, and model or supply-chain compromise, aligned to OWASP Top 10 for LLM Applications, OWASP Agentic AI guidance, and MITRE ATLAS.

Secure agents built on Microsoft Foundry (including Foundry Agent Service), and establish equivalent patterns for third-party harnesses such as Anthropic’s Claude Agent SDK.

AI Gateway & API Security

• Engineer and operate Azure APIM and AI Gateway capabilities as the policy enforcement point for model, agent, MCP, and API traffic, including authentication, authorization, rate and token limits, content safety, logging, and routing.
• Protect APIs consumed and exposed by agents with strong identity, schema validation, threat protection, and least-privilege access.
• Integrate gateway telemetry with Microsoft Sentinel and Defender for Cloud for monitoring, detection, and response.

MCP & Agent-to-Agent (A2A) Security

• Define and enforce standards for building, registering, and consuming MCP servers, including OAuth-based authorization, server allow-listing, tool and scope minimization, and supply-chain vetting.
• Establish trust, authentication, and authorization models for A2A interactions, including agent identity, delegation boundaries, and auditability of multi-agent workflows.
• Maintain an inventory of agents, MCP servers, and their connections so that exposure and blast radius are always known.

Identity & Secure Access

Design secure access to agents, MCP servers, APIs, and data using Microsoft Entra ID, managed identities, workload and agent identities, Conditional Access, and on-behalf-of flows.

Partner with the Data Security team to ensure agents only reach data they are entitled to, leveraging Microsoft Purview classification, DLP, and DSPM for AI.

Control Effectiveness & Assurance

• Define measurable control objectives and KPIs, and continuously validate that AI security controls are working as intended.
• Lead AI red teaming, adversarial testing, and threat modeling of agentic systems before and after production release.
• Build detections and automated response for AI-specific threats, and continuously improve controls based on findings, incidents, and emerging threats.