Generative Search Engine Optimization Manager

Unity Technologies

About The Position

We’re hiring a senior AI Search Engine Optimization manager to drive our shift from traditional SEO to AI-first content discovery. You’ll design, build, and operate scalable systems that make our content easily discoverable, quotable, and trusted by AI platforms (LLMs, RAG, agents, hybrid search). In the short term, you’ll audit content and infrastructure for AI retrievability, instrument citation/answer performance, and launch automation to structure and tag content for machine consumption. Longer term, you’ll build the processes and systems that enable AI SEO optimization for all content and website authors. You’ll partner with Product Marketing, Content Marketing, Web Ops, Engineering, Design, and Localization to embed AI readiness into everyday publishing, focusing on the standards and automation that make this sustainable and repeatable.

Requirements

Deep understanding of information retrieval in AI systems: embeddings, chunking, context windows, scoring, source attribution, and the signals LLMs use to select and cite content.
Demonstrated ability to design scalable content systems: metadata models, schema design, structured data, and content APIs that serve as reliable sources for machine consumption.
Strong skills in automation and operational rigor—comfortable building or specifying workflows, instrumentation, and monitoring that reduce manual optimization.
Proven experience translating complex technical concepts into clear standards and tooling that non-technical content creators can apply.
Data-driven mindset with the ability to define KPIs for AI discovery and measure impact across multiple platforms.
Excellent communication and cross-functional collaboration skills; able to influence without authority and drive consensus on standards.

Nice To Haves

Familiarity with LLM evals, automated accuracy testing, and content freshness monitoring.
Familiarity with tools such as Profound, or AirOps
Background in web architecture, sitemap strategies, crawl optimization beyond traditional SEO, or content API design.
Exposure to CMS customization and automation (e.g., schema configuration, content modeling, validation rules).
Prior work improving AI citation rates, answer quality
Comfort working in fast-paced environments where platforms change rapidly and standards must adapt.

Responsibilities

Serve as the subject-matter expert on how AI systems discover, retrieve, rank, and cite content, translating that into practical standards and automation for our publishing ecosystem.
Design and implement scalable pipelines that structure, tag, and format content for machine consumption (e.g., schema, metadata).
Create and maintain an AI performance monitoring framework that tracks citations, answer accuracy, coverage, freshness, and trust signals across key AI tools—and triggers updates when gaps are detected.
Partner with Engineering to integrate retrieval-friendly patterns (e.g., sitemap strategies, structured data, semantic markup, entity linking, content APIs) and ensure crawlability for AI systems beyond traditional bots.
Collaborate with PMM/CMMs to embed AI-optimized templates, guidelines, and “source of truth” models into authoring; provide guardrails that enable self-serve publishing without sacrificing machine readability (e.g., build an AI agent to help support PMM/CMM in authoring from the start).
Drive engineering to develop automated QA to detect broken references, outdated facts, format drift, and missing metadata; implement remediation workflows that minimize manual effort.
Build dashboards and reporting that clearly communicate AI discovery metrics to stakeholders; advocate for roadmap priorities based on measurable impact.
Stay ahead of platform changes (OpenAI, Anthropic, Google, Meta, Perplexity, and enterprise RAG patterns), updating standards and automation to ensure ongoing competitiveness.