Governance, Risk and Compliance (GRC) AI Engineer

Join a global Contract Resource Organization (CRO) where innovation meets purpose. At Worldwide Clinical Trials , we're driven by a shared commitment to improving lives through high-quality clinical research. Our teams are empowered to think creatively, take ownership, and deliver meaningful work that helps bring life-changing therapies to patients around the world.

With more than 4,000 professionals across the globe, we foster a collaborative and inclusive environment where diverse perspectives are valued, growth is encouraged, and every contribution makes an impact. Whether you're building your career or bringing years of experience, you'll have the opportunity to learn, grow, and help shape the future of clinical research.

SUMMARY: The Governance, Risk and Compliance (GRC) AI Engineer is a hands-on technical member of the Governance, Risk, and Compliance team and reports to the Senior Director of GRC. The role is responsible for engineering, configuring, integrating, and operating the technology capabilities that support the Enterprise AI Governance Framework. Working across Microsoft Purview and other approved artificial intelligence, security, data governance, compliance, and reporting technologies, the engineer will translate governance requirements into practical technical controls, workflows, monitoring, evidence, and management reporting to support AI initiatives for Information Technology. This individual will be closely partnered with the enterprise AI team, Office of the CISO, and Information Technology. The role may also work with business stakeholders to enable responsible AI adoption while protecting sensitive information and meeting security, privacy, regulatory, and customer expectations. Success requires strong technical depth, an engineering mindset, sound GRC judgment, and the ability to communicate implementation status, risks, dependencies, and decisions clearly to both technical and leadership audiences.

• RESPONSIBILITIES:
• Tasks may include but are not limited to:

• •AI governance engineering: Translate the Enterprise AI Governance Framework, policies, standards, risk criteria, and approval requirements into technical configurations, automated workflows, control checks, monitoring, and evidence.
• •Microsoft Purview administration: Configure and maintain applicable Microsoft Purview capabilities supporting AI and data governance, including data classification, sensitivity labels, data loss prevention, information protection, retention, audit, data cataloging, and compliance monitoring.
• •AI technology enablement: Evaluate, configure, integrate, and support approved AI governance and security technologies needed to discover AI use, protect enterprise data, assess risk, enforce requirements, and monitor ongoing compliance.
• •Control design and implementation: Partner with GRC, security architects, engineering teams, Privacy, Legal, and business owners to design preventive and detective controls for AI solutions, including access, data use, model lifecycle, human oversight, logging, third-party use, and exception management.
• •AI inventory and intake: Implement and maintain technical processes that support the inventory, classification, review, approval, and traceability of AI systems, models, agents, use cases, data sources, owners, vendors, and material changes.
• •Risk assessment enablement: Build and maintain workflows, templates, rules, and data connections that support AI impact assessments, security reviews, privacy reviews, third-party assessments, control attestations, and risk acceptance.
• •Data protection: Work with data and security teams to identify sensitive information used by AI solutions and implement appropriate classification, access, sharing, retention, monitoring, and loss-prevention controls.
• •Technical validation: Develop and execute test plans to confirm that AI governance controls and configurations work as intended. Document results, resolve defects, validate remediation, and maintain evidence suitable for management, audit, and regulatory review.
• •Monitoring and alerting: Establish operational monitoring for control failures, policy violations, unauthorized AI use, data exposure, configuration drift, and other governance events; investigate alerts and coordinate timely corrective action.
• •Automation and integration: Use approved scripting, application programming interfaces, connectors, workflow tools, and low-code capabilities to reduce manual effort and connect AI governance processes with enterprise systems of record.
• •Metrics and reporting: Maintain reliable data and dashboards covering AI inventory, review status, risk ratings, control coverage, exceptions, incidents, remediation, adoption, and overdue actions.
• •Status communication: Provide concise, accurate updates to the AI team, Office of the CISO, DFS, and GRC leadership, clearly identifying progress, upcoming milestones, risks, dependencies, technical decisions, and required actions.
• •Operational documentation: Maintain architecture diagrams, configuration standards, runbooks, procedures, data flows, control mappings, test records, change history, and support documentation for AI governance technologies.
• •Platform lifecycle management: Monitor Microsoft and other technology roadmaps, assess new AI governance capabilities, plan upgrades and configuration changes, and ensure solutions remain supportable, secure, and aligned with enterprise requirements.
• •Stakeholder partnership: Serve as a technical bridge among GRC, the enterprise AI team, security engineering, data governance, Information Technology, Privacy, Legal, Quality, DFS, and business teams, translating governance expectations into implementable technical outcomes.

Perform other duties as assigned. The duties and responsibilities listed above are representative of the nature and level of work assigned and are not necessarily all-inclusive.

OTHER SKILLS AND ABILITIES:

· Technical engineering: Configures enterprise platforms, troubleshoots complex issues, understands system integrations and data flows, and applies disciplined testing and change-management practices.

· AI governance fluency: Understands responsible AI principles, AI lifecycle risks, model and agent use cases, data governance, human oversight, transparency, monitoring, and third-party considerations.

· GRC judgment: Connects policies, regulatory expectations, risk statements, and control objectives to sustainable technical solutions and verifiable evidence.

· Microsoft ecosystem expertise: Works effectively across Microsoft Purview and related Microsoft security, compliance, identity, data, collaboration, automation, and AI services.

· Analytical problem solving: Breaks down ambiguous requirements, identifies root causes and dependencies, evaluates options, and recommends practical solutions.

· Communication and presentation: Explains architecture, configurations, control limitations, risks, and delivery status in language appropriate for engineers, governance teams, business stakeholders, and executives.

· Collaboration: Builds trust across functions, works effectively in a matrixed environment, and creates shared accountability among teams with different priorities and expertise.

· Independent execution: Organizes work, manages technical deliverables, communicates obstacles early, and advances assigned initiatives with limited day-to-day direction.

· Documentation discipline: Produces accurate, reusable, and audit-ready technical and governance documentation.

REQUIREMENTS:

• •Bachelor’s degree in cybersecurity, information technology, computer science, data science, engineering, risk management, or a related field. An equivalent combination of education, certification, and directly relevant experience may be considered.
• •Five or more years of progressive experience in cybersecurity, security engineering, data governance, GRC technology, cloud security, or a related technical discipline, including h