Director, Search & AI Visibility

University of Miami•Coral Gables, FL

4d•Onsite

About The Position

The Department of Marketing Technology is currently seeking a full-time Director, Search & AI Visibility to work on site in Miami. In this capacity, the incumbent will search drives for new patients, applicants, and referrals than any other channel we have. Paid and organic searches still produce most of the qualified demand for UHealth, the Miller School of Medicine, and the Academy. What's changed is what sits above the results. Clinical and academic queries increasingly return an AI-generated answer first, and only the institutions named in that answer stay in consideration. This role runs searches as one practice across paid, organic, and AI answers. Those three are now connected in practical ways. Paid query data shows what content to build. Content strong enough to rank organically is the content answer engines cite. Where AI answers cut into organic clicks, paid has to cover the gap. Run separately, they compete for budget instead of informing it. You will own the technical and content foundation for organic, the measurement system for AI visibility, and the enterprise standards and advisory function for paid search, reported on a single scorecard. Scope covers Google and Bing, Google Ads and Microsoft Advertising, AI Overviews and AI Mode, ChatGPT, Gemini, Perplexity, and Copilot. Because no one in academic medicine has yet connected AI visibility to patient acquisition with any rigor, you will build that baseline and the model behind it.

Requirements

Bachelor's degree in Marketing, Business, Communications, Digital Strategy, or a related field.
Ten or more years in search marketing spanning both SEO and paid search, including four or more years leading teams, functions, or enterprise-scale programs.
Hands-on command of paid search at scale, including experience guiding a meaningful annual search media budget and a clear point of view on automated query matching, Performance Max, and generated assets.
Deep technical SEO expertise across large, complex digital ecosystems, plus keyword and content strategy depth and local and multi-location search including Google Business Profile at scale.
Demonstrated work on AI search visibility, including prompt-level tracking and citation measurement, and a working understanding of how large language models retrieve and ground answers, sufficient to make sound calls on content structure, entity data, and crawler access without relying on vendor narratives.
Fluency with the measurement stack: Search Console, GA4 and tag management, enterprise SEO and rank tracking platforms, server log analysis, paid platform reporting, and attribution models and their limits.
Evidence of running search as a portfolio rather than a set of channels, including allocation recommendations you made and can defend.
Experience building a capability or team inside a large, complex organization, with the executive communication range to make a fast-moving technical topic decision-ready and the experimentation discipline to design tests that can fail.

Nice To Haves

Healthcare, academic medicine, higher education, or another complex, highly regulated industry, ideally multi-location or multi-brand where enterprise and local search have to work together.
Familiarity with HIPAA constraints on marketing technology and paid media targeting, web accessibility obligations, and responsible AI governance frameworks.
Hands-on experience with an enterprise SEO platform such as Semrush, Conductor, Botify, or BrightEdge.
Hands-on experience with an AI visibility platform such as Profound, Evertune, Scrunch, Otterly.AI, Peec AI, or Siteimprove.
Working knowledge of enterprise search and content discovery platforms and their impact on audience engagement and content findability.
Paid search management through a bid and portfolio platform such as Skai or Marin, and experience with a modern composable or headless content platform.
Bilingual discoverability in English and Spanish, and public thought leadership that helps attract talent to a new function.

Responsibilities

Bring paid, organic, and AI visibility into one view of search economics, and advise marketing strategists on where the next dollar should go.
Build the demand model that says what a dollar moved between brand and non-brand, between service lines, or between paid and organic is expected to return, and reconcile forecast to actual every cycle so allocation advice is grounded in measured results.
Read the three channels against each other. Use paid query data to find the demand organic and AEO should chase, use organic and citation performance to decide where paid is buying coverage we already own, and manage cannibalization deliberately rather than discovering it in a quarterly report.
Identify where AI answers are displacing organic clicks on priority terms and adjust the paid and content response before the traffic loss shows up in a ranking tool.
Own keyword and content strategy across the patient, student, referring physician, and researcher journeys, built so a single asset can rank, convert paid traffic, and be cited in an answer rather than requiring three versions of the same page.
Own conversion rather than clicks, including landing page testing, appointment request and application flows, call tracking, and the handoffs into scheduling and CRM.
Publish one search scorecard segmented by service line and academic program, built on Search Console, GA4 and tag management, rank and share of voice tracking, server log analysis, paid platform reporting, and attribution that survives scrutiny, with a live read on which peer academic medical centers are winning which terms.
Serve as the in-house paid search expert for marketing strategists across UHealth, the Miller School, and the Academy, advising on campaign architecture, keyword and audience strategy, bid strategy, and budget allocation across service lines and academic programs.
Advise on the balance between paid and organic investment, identifying where we are paying for terms we already win organically, where organic gaps justify paid coverage, and where AI answers have changed the value of a click.
Set enterprise paid search standards and review campaigns against them, covering account structure, query hygiene, negative keyword strategy, conversion tracking, and landing page quality.
Provide a tested point of view on automated query matching, Performance Max, and generated assets, including where automation earns its keep and where it spends against demand we already own.
Review agency and media partner recommendations on behalf of marketing strategists, and evaluate performance claims against measured incrementality rather than platform-reported conversions.
Equip strategists to make their own decisions well, through training, documented standards, and shared reporting rather than case-by-case approvals.
Own technical SEO requirements, including crawlability and indexation, rendering, site architecture, internal linking, page experience, canonicalization, hreflang for English and Spanish, and structured data, partnering with University IT and platform teams on implementation.
Write SEO requirements into migrations, redesigns, and platform moves as acceptance criteria in the delivery backlog, and work with delivery partners to verify them before release, so traffic performance is protected through the change rather than assessed after it.
Raise the clinical and academic authority signals that ranking systems reward, including named authors and medical reviewers, credentials, cited evidence, review dates, and clear editorial provenance.
Protect and grow provider and location discovery through local SEO, Google Business Profile at scale, accuracy of provider and location data on discovery surfaces drawn from the enterprise provider source of truth, and review volume and response, recognizing that AI Mode surfaces a materially different set of practices than the local pack and the same assets have to win in both.
Make writers and subject matter experts productive inside your standards, so quality scales without a bottleneck at your desk.
Build out the AI visibility measurement system: a governed panel of high-intent prompts, citation and recommendation share by engine, sentiment and framing, and AI referral attribution, partnering with University IT to incorporate technical crawl and access insights into business-facing AI visibility and discoverability reporting.
Track AI Overviews, AI Mode, and assistant answers as separate surfaces, because the sources they cite largely do not overlap and a single blended number will mislead the enterprise.
Make our content retrievable by systems that retrieve passages rather than pages, do not execute JavaScript, and read PDFs poorly, defining discoverability requirements for passage-level structure, answer-first formatting, and clean semantic HTML, and working with University IT and platform teams to ensure solutions support search and AI visibility objectives.
Own entity strategy for discovery, meaning one consistent machine-readable representation of the institution, its hospitals, service lines, physicians, faculty, and programs across our properties, aligned with the authoritative records in NPPES, ORCID, PubMed, and Wikidata and the third-party directories these systems cross-check.
Partner with University IT and Information Security to communicate marketing visibility requirements and evaluate the impact of crawler-access and bot-management decisions on discoverability, audience reach, referral traffic, and AI answer-engine visibility.
Own the workflow for correcting answer engines that misstate our physicians, services, locations, or outcomes, working with clinical, brand, and compliance partners.
Hold vendor claims and popular AEO tactics to the same evidence standard as everything else, run experiments with stated hypotheses and holdouts where feasible, retire what does not work, and publish internal findings so the organization learns faster than the market does.
Lead, hire, and develop a team spanning digital content, search administration, SEO, paid search, and AI visibility.
Own the vendor and platform portfolio across enterprise SEO, rank tracking, local listings, and AI visibility, and advise on paid search management platforms, partnering with IT and Procurement on selection, consolidation, and renewal.
Lead AI adoption and capability development within Marketing and Communications, aligned with enterprise AI platforms, standards, and guidance, including curriculum, prompt library, and a tiered path from first use to power user, measured by adoption and time saved rather than attendance.
Serve as Marketing's primary liaison to University IT on matters affecting search, discoverability, and AI visibility.
Hold this work to the institutional standards a regulated environment requires, including HIPAA-aware handling of marketing data, tracking technology practices that distinguish authenticated from unauthenticated experiences, WCAG 2.1 AA conformance, and human review before AI-assisted content reaches a patient-facing surface.
Serve as Marketing's voice on the search and answer engine landscape, briefing senior leadership and turning a fast-moving technical field into clear investment decisions.