Director, AI Security

Omnicell•Grapevine, TX

11d•$213,197 - $236,886

About The Position

Omnicell is seeking a Director, AI Security, to establish and lead the enterprise capabilities that enable responsible AI adoption. The role defines strategy, architecture, governance, and operational controls to secure machine learning, generative AI, LLMs, AI agents, copilots, and autonomous systems throughout their lifecycles, protecting sensitive data, customers, patients, and the business while enabling AI at scale. This role owns the security architecture and control environment for AI systems as enterprise platforms and AI agents as autonomous identities that access data, invoke tools, and act on the organization’s behalf. It is broader than AI governance or compliance: the Director is responsible for preventing unmanaged authority, uncontrolled data exposure, and unacceptable enterprise, regulatory, or patient-safety risk. During the first 12 months, the Director will establish the enterprise AI security strategy, governance, and operating model; an AI and agent inventory with identity and authorization standards; reference architectures for secure GenAI, RAG, MCP, AI platforms, agents, and model services; threat-modeling, red-team, vendor/model assessment, and AI detection and response capabilities; and incident-response playbooks. The role will extend the enterprise security reference architecture, integrate AI security with the Architecture Review Board (ARB) and enterprise risk register, establish executive metrics and risk reporting, and develop a joint operating model with Product Security for AI involving connected devices. It will also establish cyber-physical and connected-device controls for AI embedded in or interfacing with Omnicell pharmacy automation, including IEC 62443/Purdue-aligned segmentation and fail-safe or human-approval requirements for device- and medication-affecting decisions. Success is measured through inventory and pre-production review coverage, red-team coverage, remediation and detection/containment times, and reduced unauthorized AI use. The role works collaboratively across Security, Engineering, Data, Privacy, Legal, and Quality/Regulatory. Work is primarily computer-based, with flexible hours for critical security decisions and incidents, frequent collaboration across time zones, and approximately 15–20% travel. The stated good-faith base salary range is $213,196.95–$236,885.50, plus annual bonus and equity eligibility; actual pay depends on skills, experience, and location.

Requirements

15+ years of progressive experience in cybersecurity, security architecture, engineering, or technology risk.
5+ years leading enterprise security architecture, engineering, product, cloud, application, or AI security capabilities.
Experience operating within a formal enterprise security architecture practice, including ARB participation and reference architecture ownership; SABSA, TOGAF, or equivalent experience.
Experience designing controls spanning identity, network, data, and application layers across hybrid and multi-cloud estates.
Strong knowledge of generative AI, LLMs, agentic AI, RAG, and vector databases, with the ability to translate AI risk into practical architecture and technical controls.
Deep understanding of IAM, privileged access, Zero Trust, cloud security, application/API security, threat modeling, and security operations.
Experience in healthcare, medical-device, or another highly regulated environment.
Strong executive communication and cross-functional influence.
Experience with OT, ICS, IoMT, or connected medical-device environments, or close partnership with product security in a device manufacturer, healthcare delivery organization, or comparable cyber-physical context.
Working knowledge of IEC 62443, NIST SP 800-82, FDA premarket/postmarket cybersecurity guidance, and clinical network segmentation practices.

Nice To Haves

Bachelor’s or master’s degree in a related field, or equivalent practical experience.
CISSP, CCSP, CISM, SABSA, TOGAF, cloud security certifications, IAPP AIGP, or GICSP (OT) certification.
Experience securing production enterprise platforms and technologies such as OT/IoMT, AI, Azure, OpenAI, Copilot, Bedrock, Vertex AI, Anthropic, Databricks, LangChain, or MCP.
Experience with AI security capabilities such as gateways, posture management, red teaming, model scanning, or non-human identity.
Experience securing OT, ICS, IoMT, or connected medical-device environments, including IEC 62443, NIST SP 800-82, FDA cybersecurity guidance, and clinical network segmentation.
Familiarity with OWASP LLM guidance and MITRE ATLAS.
Experience building AI inventories, agent registries, or AI incident-response programs.
GICSP or equivalent OT credential.

Responsibilities

Define and lead the enterprise AI security strategy, operating model, governance, and roadmap; oversee the function’s performance, resources, and capabilities.
Extend and align enterprise security architecture and standards to AI technologies, including appropriate controls, risk management, and integration with broader security frameworks.
Establish and manage AI security controls, architectures, and operational practices across AI platforms, applications, agents, and supporting technologies, supporting secure development, deployment, and monitoring.
Partner with product and technology teams to secure AI-enabled and connected systems, applying appropriate safeguards, risk-management practices, and regulatory considerations.
Lead AI security governance, risk oversight, and compliance activities, aligning with applicable security, privacy, regulatory, and industry frameworks.
Establish AI and AI-agent inventories, agent identity and authorization standards, reference architectures, threat-modeling methods, red-team programs, and vendor/model assessment processes.
Establish AI Detection & Response capabilities and incident-response playbooks.
Integrate AI security reference architecture with the ARB and enterprise risk register, including identity fabric, Zero Trust segmentation, and dataflow and trust-boundary standards.
Establish a joint operating model with Product Security for AI that touches connected devices, along with executive metrics and risk reporting.
Establish CPS and connected-device security controls for AI embedded in or interfacing with Omnicell pharmacy automation, including segmentation and fail-safe/human-approval requirements for device- and medication-affecting decisions.
Collaborate across Security, Engineering, Data, Privacy, Legal, and Quality/Regulatory; develop talent and organizational capability; enable responsible AI adoption while reducing enterprise, regulatory, and patient-safety risk.