Lead AI Security Engineer

Description

We are seeking a Lead AI Security Engineer to support the Security team's AI governance initiatives, focusing on evaluating AI capabilities, conducting security assessments, developing secure AI integrations, and supporting enterprise AI adoption. This role collaborates closely with a US Eastern Time-based Security team, with EMEA-based candidates welcome due to time-zone alignment. Responsibilities Evaluate and approve AI skills, agents, connectors, and MCP integrations against defined security and risk criteria Design and build custom MCP servers, connectors, and integrations for approved business use cases Conduct security reviews of Claude Enterprise, Microsoft 365 Copilot, and related AI platform capabilities Assess connectors and integrations for data exposure, permissions, identity and security controls, auditability, and implementation risks Help develop and maintain AI governance standards, review processes, and risk assessment frameworks Provide architecture recommendations and implementation guidance to ensure secure AI adoption Provide guidance on cost optimization for consumption-based AI products Requirements 5+ years of experience in AI governance initiatives within enterprise environments Expertise in MCP (Model Context Protocol) implementations and integrations Knowledge of Cloud Security, AI Security, and Cybersecurity practices Proven working experience collaborating with cross-functional security teams on AI adoption projects English proficiency at B2 level or higher Nice to have Background in Enterprise Security Architecture and AI Security Risk Assessment Familiarity with Claude Enterprise, Microsoft 365 Copilot, and Microsoft Copilot Studio Skills in API Development & Integrations, Identity & Access Management (IAM), and Data Security & Protection Understanding of Security Controls & Auditability, AI Connectors & Agents, and Risk Assessment Frameworks Expertise in Secure AI Architecture & Implementation Guidance, Custom MCP Server Development, and MCP Connectors & Integrations Knowledge of AI Governance Framework Development, Enterprise AI Platform Security Reviews, and AI Cost Optimization Familiarity with Consumption-Based AI Products, AI Adoption & Responsible AI, and AI Skills Development Understanding of Security Review Processes and Enterprise Integration Architecture

Requirements

• 5+ years of experience in AI governance initiatives within enterprise environments

• Expertise in MCP (Model Context Protocol) implementations and integrations

• Knowledge of Cloud Security, AI Security, and Cybersecurity practices

• Proven working experience collaborating with cross-functional security teams on AI adoption projects

• English proficiency at B2 level or higher

Responsibilities

• Evaluate and approve AI skills, agents, connectors, and MCP integrations against defined security and risk criteria

• Design and build custom MCP servers, connectors, and integrations for approved business use cases

• Conduct security reviews of Claude Enterprise, Microsoft 365 Copilot, and related AI platform capabilities

• Assess connectors and integrations for data exposure, permissions, identity and security controls, auditability, and implementation risks

• Help develop and maintain AI governance standards, review processes, and risk assessment frameworks

• Provide architecture recommendations and implementation guidance to ensure secure AI adoption

• Provide guidance on cost optimization for consumption-based AI products

Seniority

• Lead

Nice to have

• Background in Enterprise Security Architecture and AI Security Risk Assessment

• Familiarity with Claude Enterprise, Microsoft 365 Copilot, and Microsoft Copilot Studio

• Skills in API Development & Integrations, Identity & Access Management (IAM), and Data Security & Protection

• Understanding of Security Controls & Auditability, AI Connectors & Agents, and Risk Assessment Frameworks

• Expertise in Secure AI Architecture & Implementation Guidance, Custom MCP Server Development, and MCP Connectors & Integrations

• Knowledge of AI Governance Framework Development, Enterprise AI Platform Security Reviews, and AI Cost Optimization

• Familiarity with Consumption-Based AI Products, AI Adoption & Responsible AI, and AI Skills Development

• Understanding of Security Review Processes and Enterprise Integration Architecture