Executive Director, AI Solutions Engineering

The University of Miami Health System (“UHealth”) IT Department has an exciting opportunity for a full-time Executive Director of AI Solutions Engineering to work onsite in Miami.

The Executive Director of AI Solutions Engineering provides strategic leadership for the University's enterprise AI engineering function, defining the technical vision, operating model, governance framework, and roadmap for AI-enabled solutions across the institution.

This role is responsible for building and leading a high-performing AI engineering organization that partners with academic and administrative units to design, develop, and deploy scalable, secure, and responsible AI solutions that advance institutional priorities. The Executive Director oversees the enterprise AI solutions portfolio, establishes engineering standards and delivery practices, and ensures successful execution through a team of engineering leaders and technical professionals.

The ideal candidate will lead the development and deployment of AI agents and enterprise AI capabilities while recruiting, mentoring, and managing a growing team of AI engineers. Positioned at the intersection of technical leadership and people leadership, this role requires both hands-on involvement in coding, prototyping, and solution development, and accountability for team performance, processes, and outcomes.

• Embed with internal business and engineering teams to map their workflows, identify automation opportunities, and scope agent use cases with measurable ROI.

• Architect and build production-grade AI agents and multi-step agentic workflows using LLM APIs(Anthropic, OpenAI, etc.), orchestration frameworks, and tool/function calling, integrated with our internal systems, data stores, and third-party SaaS.

• Design and maintain evaluation suites, guardrails, and observability for deployed agents — catching regressions, hallucinations, and cost overruns before they reach users.

• Own deployments end to end: from rapid prototype through hardening, security review, rollout, monitoring, and iteration.

• Manage model selection, prompt/context engineering standards, and API cost optimization across providers.

• Hire, mentor, and manage a team of AI/forward deployed engineers; conduct performance reviews, career development, and capacity planning.

• Define the team’s operating model: intake and prioritization of agent requests from other departments, delivery standards, maintenance ownership, and SLAs.

• Establish reusable platform components (agent templates, shared tooling, eval harnesses, security patterns) so each new agent ships faster than the last.

• Partner with department leaders and executives to build the AI adoption roadmap, communicate impact, and report on outcomes (hours saved, error reduction, cost avoided).

• Set governance standards for safe and responsible agent deployment, including data privacy, access control, auditability, and human-in-the-loop design.

This list of duties and responsibilities is not intended to be all-inclusive and may be expanded to include other duties or responsibilities as necessary.

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred)

• 7+ years of software engineering experience, including 2+ years leading or managing engineers (formal management or strong tech-lead experience).

• Production experience with LLMs: advanced prompt/context engineering, agent development, tool use/function calling, RAG, and evaluation frameworks.

• Strong full-stack or backend engineering skills (e.g., Python and/or Type Script), with experience integrating APIs, databases, and cloud infrastructure (GCP, AWS, or Azure).

• Demonstrated success working directly with non-engineering stakeholders — translating ambiguous business problems into shipped technical solutions.

• Track record of owning systems in production: monitoring, incident response, iteration based on real usage.

• Excellent communication skills; able to present to executives and pair with analysts in the same week.

• Experience with agent orchestration frameworks (Lang Graph, CrewAI, Auto Gen, Claude Agent SDK, or similar) and MCP-style tool…