Enterprise AI Enablement Lead

About the role

Jackson Healthcare and our family of companies provide healthcare systems, hospitals and medical facilities of all sizes with the skilled and specialized labor and technologies they need to deliver high quality patient care and achieve the best possible outcomes - while connecting healthcare professionals to the temporary engagements, contract assignments and permanent placement employment opportunities they desire. Headquartered in metro Atlanta, we're powered by more than 2,600 associates and over 20,000 clinician providers covering all 50 U.S. states. Our mission is to improve the delivery of patient care and the lives of everyone we touch. This includes the patients, clinicians and healthcare executives we work with through our companies every day, as well as our communities, the nonprofit organizations we support and each associate who is part of our family. We're always looking to add new talent to our teams. We value diverse professionals at all levels and across multiple disciplines and areas of expertise, who have strong leadership skills, align with our culture, and are committed to excellence. POSITION OVERVIEW The Enterprise AI Enablement Lead is a senior individual contributor responsible for designing, building, and operationalizing AI- and agent-enabled solutions that support real business workflows across Jackson Healthcare and its companies. This role goes beyond experimentation or associate education. It requires applied value driven use case assessment, problem-solving, architectural judgment, and hands-on execution to translate emerging AI capabilities into secure, scalable, and reusable enterprise solutions. The Enterprise AI Enablement Lead serves as a subject matter expert in agentic AI application, partners closely with business leaders, infrastructure, identity, data, and application teams, and helps establish the technical and operational foundation required for responsible AI adoption at scale. ESSENTIAL RESPONSIBILITIES AI Solution Engineering & Architecture Identify and translate ambiguous business problems and process opportunities into implementable AI solutions with clear ownership, outcomes, and operational constraints. Design, build, and deploy AI- and agent-enabled solutions embedded in real enterprise workflows across multiple business lines. Define and apply practical reference architectures for agentic AI, including task orchestration, decision boundaries, escalation patterns, and human-in-the-loop controls. Evaluate and apply no-code, low-code, and full-code approaches appropriately based on risk, scale, and maturity requirements. Agent Enablement & Execution Lead hands-on implementation of agentic AI patterns, including multi-step reasoning, tool use, and workflow coordination. Partner with application and platform engineers to integrate AI agents with enterprise systems, automation platforms, and data sources. Establish clear distinctions between experimentation, pilot solutions, and enterprise-ready deployments. Enable responsible citizen self-service agent development where appropriate by promoting awareness, fluency, and enthusiasm and helping to create the necessary foundational scaffolding to support it. Security, Governance & Responsible Use Alignment Partner with identity, security, and governance teams to embed execution guardrails directly into AI solution design. Ensure AI agents operate within defined authorization, least-privilege, and auditability constraints. Contribute to the development of standards, patterns, and documentation that support secure and governed AI deployment. Enablement, Reuse & Enterprise Scaling Convert successful AI implementations into reusable patterns, templates, and guidance for broader enterprise adoption. Enable other technical teams and business partners through shared artifacts, examples, and applied guidance. Support cross-functional initiatives where AI capabilities intersect with infrastructure, data, automation, and application platforms. Collaboration & Communication Communicate AI solution designs, constraints, and outcomes clearly to technical teams, business partners, users, and leadership. Serve as a technical advisor on AI capabilities and limitations across enterprise initiatives. Participate in architectural and change reviews to assess AI impact on systems, workflows, and risk posture. QUALIFICATIONS - EDUCATION, WORK EXPERIENCE, TECHNICAL EXPERTISE REQUIRED Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field - OR - equivalent combination of education and experience. 7+ years of overall technology experience with demonstrated hands-on responsibility for production-grade solutions. Demonstrated experience leading the identification, evaluation and selection of business processes and workflows for AI enablement across multiple business or knowledge domains. Proven experience developing and deploying AI-driven or automation-enabled solutions in enterprise env