Technical SEO Engineer

Role at a glance

We are rebuilding our web presence on the same principle we deliver on. The site is a technical asset, not a brochure, and it has to be legible to crawlers, to answer engines, and to the AI agents that increasingly stand between a CTO and a shortlist.

Our category claim is technical. The people we sell to are technical. But our site currently under-performs on exactly the dimensions our buyers would judge us on: rendering behaviour, structured data, Core Web Vitals, and crawl efficiency across a large migration of legacy URLs.

We are not hiring a keyword strategist. We are hiring the person who owns the machine-readable layer of Mactores, meaning the schema graph, the render path, the crawl budget, the redirect map and the performance envelope, and who can sit with an engineer, read the framework code, and say precisely what needs to change and why. The short version: if the fix requires a pull request, you should be able to specify it, review it, and defend it in code review, not file a ticket and hope.

This is a senior individual-contributor seat with high autonomy and direct influence over engineering priorities. You get ownership of a channel that matters to the business, an engineering-led firm that will actually implement what you specify including agent-assisted implementation, and compensation benchmarked to senior engineering rather than to marketing. It is the wrong role if your technical SEO work has been running an audit tool and forwarding the PDF to a developer, if you need someone else to tell you whether a page is server-rendered, or if you are looking to manage a team rather than do the work.

What you'll do?

• Design and maintain a connected Schema.org graph across the site covering Organization, Service, Article, FAQPage, BreadcrumbList, Person, Event, JobPosting, VideoObject and Dataset, using stable @id references so entities link rather than repeat.
• Decide JSON-LD placement and injection strategy, server-rendered versus tag-managed versus edge-injected, and defend the trade-offs. Debug validation and eligibility issues down to the property level: required versus recommended fields, nesting depth, sameAs disambiguation, and why markup that passes the validator still fails to earn a rich result.
• Extend the graph for AI and answer-engine visibility. Entity consistency, citation-friendly content structure, llms.txt-style surfaces, and how our knowledge graph reads to a retrieval system rather than only to a blue-link ranking system. Monitor structured-data health continuously and treat markup regressions as production incidents.
• Own Core Web Vitals (LCP, INP, CLS) as an engineering target, using field data (CrUX, RUM) as the source of truth and lab tooling (Lighthouse, WebPageTest, trace analysis) as the diagnostic.
• Take a slow page apart: critical rendering path, render-blocking resources, hydration cost, main-thread long tasks, third-party script budget, font loading, image formats and sizing, caching and CDN behaviour.
• Translate the diagnosis into specific, implementable engineering guidance. The component to refactor, the bundle to split, the payload to defer, the header to set, and then sit with the developers through implementation and verification. Establish performance budgets and CI-level guardrails so wins do not silently regress on the next deploy.
• Work credibly with modern stacks and edge delivery: Next.js, React and Astro-class frameworks, SSR, SSG and ISR trade-offs, CDNs and edge workers, image pipelines.
• Own JavaScript SEO. Client-side versus server-side rendering, hydration, dynamic rendering, the two-wave indexing model, and diagnosing what a crawler actually receives versus what a browser shows.
• Run crawl and index architecture at scale. Log-file analysis, crawl-budget allocation, faceted navigation and parameter handling, pagination, canonical strategy, index bloat, soft-404 and duplication patterns.
• Own technical SEO through migration and replatforming. Redirect mapping and validation, URL taxonomy design, staged cutovers, and pre and post monitoring that catches losses in days rather than quarters.
• Handle internationalization and multi-region delivery: hreflang at scale, regional CDN behaviour, and geo-routing that does not break canonicalization.
• Handle everything a marketing site accretes, including gated content, headless CMS quirks, single-page app routes, programmatic page generation, embedded tools and calculators, video and event content, without losing indexability.
• Instrument what matters. Search Console API, GA4 and server-side analytics, crawler exports from Screaming Frog, Sitebulb or equivalent, and log data, joined and analyzed in SQL or Python rather than eyeballed in a dashboard.
• Build the reporting that separates a real technical regression from an algorithm update from a seasonal dip, and say which one it is with evidence. Bring that technical read into content and IA decisions: where an entity needs its own page, where consolidation beats creation.

What we're looking for?

• A degree in Computer Science, Software Engineering, Information Technology or a closely related engineering discipline. This role requires someone who was trained to read and reason about code, not someone who picked up HTML alongside marketing work.
• 6+ years in a dedicated SEO role, with the majority of that time spent on the technical side rather than general digital marketing with SEO as one of several responsibilities.
• Demonstrable in-depth Schema.org expertise. You have designed a multi-entity graph from scratch and can explain the choices you made and what they earned.
• A proven record of guiding development teams through performance optimization, with before and after field data and a clear account of what you specified versus what the engineers built.
• Working proficiency in HTML, CSS and JavaScript, comfort reading a modern JS framework codebase, fluency with Git and pull-request review, and the ability to write Python or SQL for data work.
• Experience owning technical SEO through at least one large site migration or replatform.
• Written communication strong enough that an engineering lead reading your ticket knows exactly what to do and why it matters.
• Sustained availability for daily overlap with US hours.

You'll be preferred if you:

• Come from B2B technology or enterprise services, with long sales cycles, technical buyers and low-volume high-intent search.
• Are familiar with cloud, data or AI subject matter, and can hold a conversation about AWS, data platforms or agentic systems without a translator.
• Have hands-on experience with AI and LLM visibility, meaning how content gets retrieved, cited and surfaced by answer engines and agents.
• Have built your own tooling: crawlers, API pipelines, monitors, or scripts that replaced a manual process.
• Have done edge-compute or CDN-level SEO work in Cloudflare Workers, Lambda@Edge or similar.