Executive Director, AI Solutions Engineering

Core Responsibilities

• 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.

Minimum Qualifications

• 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 TypeScript), 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.
• Excellent communication skills; able to present to executives and pair with analysts in the same week.
• Experience with agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Claude Agent SDK, or similar) and MCP-style tool integration preferred.
• Prior forward-deployed, solutions engineering, or consulting experience embedding with customer or internal teams preferred.
• Experience standing up an AI enablement or internal automation function from scratch preferred.
• Experience in a regulated or data-sensitive domain (fintech, tax, healthcare), including PII handling and compliance preferred.

Benefits

The University of Miami offers competitive salaries and a comprehensive benefits package including medical, dental, tuition remission and more.

Pay

Competitive salary commensurate with experience.

Schedule

Full-time.