Sr. Digital Marketing Manager II, Web Platform Optimization, SEO & AI Search

LinkedIn•San Francisco, CA

13h•$170,000 - $278,000•Hybrid

About The Position

LinkedIn's web platforms are crucial for how professionals discover, trust, and engage with information, increasingly through AI-powered search and large language models. This role is responsible for owning how LinkedIn’s web platforms are structured and optimized for AI-era discovery at scale. Sitting within Web Marketing, this role ensures that Adobe Experience Manager (AEM) implementations, across marketing sites, microsites, and the Help Center, are designed to maximize crawlability, performance, accessibility, taxonomy and data tagging, structured data, and AI/LLM visibility. The focus is on building durable standards, automated validation, and scalable systems so optimization is embedded into operations, rather than addressed through one-off fixes. The role partners closely with SEO, Content, Web Engineering, MarTech, and SSO teams, and plays a key advisory role during major platform transitions.

Requirements

Bachelor's degree in Marketing, Business, or related field AND 7+ years of experience in web marketing, performance marketing, user experience, technical SEO, search and discovery optimization, or equivalent experience.
7+ years of experience in technical SEO fundamentals, including crawlability and indexation, metadata, structured data, and redirect strategy.
7+ years of experience working with enterprise content management systems (CMS) and translating optimization requirements into scalable templates, components, or standards.

Nice To Haves

3+ years direct experience with Adobe Experience Manager (AEM) and/or AEM Guides, including structured content models (e.g., DITA) and localization workflows at scale.
Experience advising on or leading SEO-sensitive platform migrations (e.g., CMS changes, URL restructures, redirect strategies at scale).
Familiarity with AI-era discovery concepts such as AEO, AI Overviews, and LLM visibility, and how content structure, taxonomy, and markup influence AI systems.
Strong understanding of accessibility and performance considerations that impact discoverability (e.g., core technical vitals, rendering, page speed).
Experience building repeatable standards and governance models that reduce technical debt over time.
Experience partnering with automation or tooling initiatives to systematize optimization workflows (e.g., automated auditing, validation, prioritization).
Proven ability to influence and drive alignment across cross-functional partners without direct authority, and to translate technical concepts into clear, actionable guidance for non-technical stakeholders.

Responsibilities

Own platform-level search and AI discovery optimization across LinkedIn web properties, including marketing sites, microsites, and the Help Center.
Define and enforce scalable technical standards and governance across AEM Sites and AEM Guides to maximize discoverability–ensuring crawlability, accessibility metadata and schema quality, taxonomy and tagging consistency, redirect integrity, URL hygiene, and overall site health for both traditional search and AI/LLM visibility.
Monitor site health and core technical vitals, identify gaps and opportunities, and translate findings into clear, prioritized action plans with SEO, Content, Web Engineering, MarTech, and SSO partners.
Serve as a technical advisor and partner for major platform transitions—especially the Help Center migration from Lithograph to AEM Guides—ensuring migrations maintain traffic stability, improve long-term discoverability, and avoid introducing technical debt.
Guide migration-critical decisions and cleanup efforts, including redirect strategy, remediation of broken or legacy pages, metadata/schema consistency, and recommendations for pruning thin or outdated content.
Build (or drive the build of) automated validation systems and AI-assisted / agentic workflows that continuously monitor site health and optimization quality, enabling proactive optimization across large page inventories.
Partner on AI automation efforts (e.g., Claude-based workflows) to operationalize repeatable optimization processes, while retaining internal ownership, governance, and review.
Act as the internal point of accountability for platform-level optimization standards across Web and Help, producing documentation and guidance that enable teams to operate efficiently within shared standards.
Lead integration of AEM with internal and external platforms, APIs, and automation tooling to scale optimization (e.g. centralized schema management, Adobe SEO optimizer, and validation layers), reducing manual effort and ensuring consistency across large page inventories.