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

🔥 Posted 54 days ago
San Francisco, CA On-site Full-time North America
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About this role

LinkedIn hiring to optimize LinkedIn.com itself for SEO and AI search, a notable bit of self-referential proof that even the platforms are treating this as core infrastructure work now, not a marketing afterthought.

AI Replacement Risk

LOW

Full job description

Sourced directly from LinkedIn's original listing.

LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

This role will be based in San Francisco Bay Area or NYC.

LinkedIn’s web platforms play a critical role in how professionals discover, trust, and engage with information - increasingly through AI‑powered search and large language models, not just traditional search engines.

We’re looking for a Web Platform Search Optimization Lead to own how LinkedIn’s web platforms are structured and optimized for AI‑era discovery at scale. Sitting within Web Marketing, this role ensures that our 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.

For this platform‑level optimization role, you’ll focus on building durable standards, automated validation, and scalable systems so optimization is embedded into how we operate, not addressed through one‑off fixes after the fact. The role partners closely with SEO, Content, Web Engineering, MarTech, and SSO teams, and plays a key advisory role during major platform transitions such as the Help Center migration from Lithograph to AEM Guides.

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.

Basic Qualifications

  • 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.

Preferred Qualifications

  • 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.

Suggested Skills

  • AI Fluency
  • Strategic Thinking
  • Cross-Team Collaboration
  • Stakeholder Management
  • Data Analysis

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $170,000 to $278,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.

Equal Opportunity Statement

We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.

If you need a Reasonable Accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us and describe the specific Accommodation requested for a disability-related limitation.

Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

  • Documents in alternate formats or read aloud to you
  • Having interviews in an accessible location
  • Being accompanied by a service dog
  • Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.

San Francisco Fair Chance Ordinance ​

Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement ​

As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.

Global Data Privacy Notice and Compliance Posters for Job Candidates

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.

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AI Replacement Risk, explained

We rate every role on how much of the day-to-day work could plausibly be done by current AI tools within the next year or two. It's a judgment call, not a hard science, based on three questions:

Task repeatability — is the work mostly repeatable execution (drafting, formatting, routine audits), or judgment-heavy (strategy, negotiation, prioritization)?
Precedent — are AI tools already doing a meaningful chunk of this work well today, in production, somewhere?
Accountability — does the role carry a decision or relationship someone has to own, not just an output that has to exist?

LOW

Mostly judgment, negotiation, or ownership work. AI assists, it doesn't replace.

MED

A real mix of judgment and repeatable execution. Expect the repeatable half to keep shrinking.

HIGH

Mostly production or output work, with real AI precedent already in the wild.

This is our own read, not a scientific index. Treat it as a conversation starter before you apply, not a scorecard.