AI Security Engineer

Why Pretium Enterprise Services?

With expert business service capabilities, Pretium Enterprise Services (“PES”), is integral to the growth, innovation, and transformation of its global operating companies. Partnering with internal and external businesses and stakeholders to rapidly unlock value for its customers, PES delivers with excellence and ownership, enabling scalable growth.

Job Overview

Pretium Enterprise Services (PES) is seeking an AI Security Engineer to help build and implement our enterprise AI security program. This hands-on role within Infrastructure & Cybersecurity will assess our current posture, develop a prioritized roadmap, and implement controls supporting secure AI adoption across Pretium and its operating companies.

Working with technology teams, developers, business owners, Legal, and Compliance, you will secure enterprise AI platforms and the AI capabilities embedded across business applications, establishing shared standards and delivering practical protections for enterprise data, AI agents, and integrations.

This role is hybrid three days a week in our office located in Scottsdale, Arizona (preferred location). Other locations that will considered: Dallas, Texas; Charlotte, North Carolina and California.

What You’ll Do

Assess AI usage, data flows, and control gaps across operating companies; maintain an inventory of AI platforms, embedded capabilities, agents, integrations, and accountable owners.

Develop and execute the AI security roadmap, including priorities, milestones, dependencies, and measurable outcomes. Establish enterprise minimum controls and repeatable intake, onboarding, review, and exception processes.

Configure and validate platform controls, including SSO, provisioning, role-based access, approved models, sharing restrictions, and connector permissions across web, desktop, developer tools, and APIs.

Implement and tune data loss prevention and AI guardrails. Work with data owners to address oversharing, protect sensitive information, and maintain data boundaries between operating companies.

Secure AI agents, plugins, connectors, and Model Context Protocol (MCP) integrations through least privilege, credential protection, restricted tool access, and approvals for high-impact actions.

Partner with cloud and development teams to secure Bedrock and other AI workloads through identity controls, encryption, secrets management, network protections, and automated configuration checks.

Perform threat modeling and security testing for AI applications and retrieval-augmented generation (RAG), including prompt injection, data disclosure, unauthorized actions, retrieval permissions, and guardrail bypass. Track remediation and retest changes.

Integrate available audit APIs, cloud logs, and agent telemetry with enterprise monitoring. Validate coverage, address gaps, and develop detections and incident response procedures with security operations.

Implement approved retention, access, and deletion requirements with Legal and Compliance, including protection of sensitive information in prompts, outputs, and logs.

Evaluate AI vendors and embedded AI features for data handling, model training use, permissions, retention, and auditability. Test security solutions and recommend tools that integrate with enterprise capabilities.

Publish technical standards and implementation guidance; support operating company adoption and report roadmap progress, control coverage, exceptions, and remediation to leadership.

Who We’re Looking For

Five or more years of experience in security engineering, cloud security, application security, or a related discipline, with demonstrated hands-on implementation of enterprise controls.

Practical experience securing an enterprise AI platform or AI-enabled application, including identity, data access, integrations, or monitoring, and testing control effectiveness.

Strong foundations in IAM, least privilege, data protection, API security, secrets management, and security logging, with hands-on AWS or Microsoft cloud experience.

Working knowledge of LLM and agent security risks, including prompt injection, data leakage, excessive permissions, and unsafe tool execution. Familiarity with NIST AI Risk Management Framework and OWASP guidance is preferred.

Ability to automate controls and integrations using Python, PowerShell, or a comparable language and work with REST APIs, logs, and connected systems.

Ability to turn evolving requirements into a practical roadmap and deliver work through implementation, documentation, and operational handoff. Strong communication and collaboration across operating companies and control functions.

Experience with Claude Enterprise, ChatGPT Enterprise, Microsoft 365 Copilot, AWS Bedrock, Microsoft Entra, Purview, DLP, or SIEM platforms is preferred; expertise in every platform is not required.

Experience with MCP integrations, AI agents, RAG, adversarial testing, or infrastructure as code is preferred, as is experience in a shared-services organization, financial services, or another regulated industry.

What We Offer

This position offers the opportunity to join a collegial, entrepreneurial firm committed to the personal and professional growth of its team members and to maintaining a positive, encouraging work environment where people enjoy working together. The company offers a comprehensive benefits and perks package, including:

401(k) plan with an employer match

Health, dental, vision and life insurance

Paid Time Off (PTO)

11 firm holidays

Hybrid office/work from home arrangement

Annual year-end bonus eligible

Pretium Enterprise Services is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, gender, gender identity or expression, genetic information, marital status, sexual orientation, national origin, disability, age, veteran status, or any other characteristic protected by federal, state, or local law.