The posting
About the role
We're hiring a Growth Marketer to own the two engines that turn marketing spend into pipeline: organic visibility (SEO plus answer-engine and generative-engine optimisation, AEO/GEO) and paid campaign performance. You'll audit both, fix what leaks, scale what works, and be judged on qualified pipeline — not clicks, form fills or impressions.
What you'll own
You'll run two loops — organic and paid.
Organic visibility: SEO, AEO and GEO
- Measure how AI assistants (ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews) answer our buyers' questions, per market: are we cited, which sources they draw on, what they say about us, and which competitor wins the answer.
- Maintain the tracked prompt set across three buyer intents — discovery ("best X for Y"), alternatives ("alternatives to [competitor]") and sentiment ("[brand] reviews", "[brand] vs [competitor]") — built from observed queries, not guesses.
- Trace every negative or inaccurate AI answer to its root source (a review site, a directory listing, an employer-review page, a competitor page) and fix it there with dated, factual content.
- Ship content engineered to be quoted: answer-first pages, comparison and alternatives pages, FAQs with schema, and original data stories.
- Own technical readiness: structured data, llms.txt, AI-crawler rules, canonicals, redirects and page speed — spec the change, then verify it is live.
- Grow the off-site footprint AI engines trust: review-platform profiles and their category placement, consistent directory listings, tier-1 trade-media coverage, and disclosed community answers on forums like Reddit and Quora.
Paid performance
- Audit campaigns end to end — spend, then CRM contacts, MQLs, SQLs, opportunities and closed-won — and report true cost per SQL, per opportunity and per won deal next to the platform's own numbers.
- Find where junk leads enter (broad match, loose location settings, auto-generated ads, network expansion) and close each leak structurally, not one lead at a time.
- Read the account change history and attribute a shift in performance to a change only when timing and mechanism both support it.
- Keep bidding and conversion goals healthy: no low-volume goal running alone, staged goal migrations, budget raised in measured steps.
- Compare who is served, who clicks and who converts by age, device, audience segment and geography — then against who actually becomes pipeline.
- Publish a Stop / Start / Continue plan each cycle: what to kill, what to scale, and the one fix for each near miss.
Measurement and operating rhythm
- Own a weekly three-line scoreboard (organic clicks week on week, biggest losing pages, AI-citation movers) and a monthly full report.
- Keep GA4 key events, UTMs and CRM source fields clean enough that paid and organic results can be trusted.
- Write a predicted impact for every recommendation, then grade it honestly a month later.
- Brief and verify agencies against their contracted scope, measured on outcomes rather than activity counts.
- Build repeatable, AI-assisted workflows (LLMs, API connectors, light scripting) that turn manual audits into weekly routines.
- Work daily with sales development and sales so leads are routed, worked fast and fed back as quality signals.
What you'll bring
You've run both paid and organic yourself, hands on keyboard, and you can show what your work did to pipeline.
- 4–7 years in B2B growth, performance or SEO roles, at least two of them in B2B SaaS or another long-sales-cycle technology business.
- Hands-on Google Ads (Search, Demand Gen, YouTube) and LinkedIn Ads, accountable for a meaningful monthly budget.
- Strong technical SEO: Search Console, structured data, crawling and indexing, redirects and migrations. You can turn a crawl report into a spec a developer acts on.
- Working knowledge of AEO/GEO — how AI assistants choose and cite sources, and how to measure visibility across repeated prompt runs. You've run an AI-visibility audit, or can walk us through how you would.
- CRM fluency (HubSpot, Salesforce or similar): lifecycle stages, lead status, source fields and UTMs. You can build the report that ties spend to SQLs and deals.
- Analytical discipline: comfortable in GA4, spreadsheets and basic SQL, and clear on the difference between a change that coincided with a result and one that caused it.
- AI-native working habits: you already use LLMs, connectors and simple automations to run audits, reports and drafts — and you check what they produce.
Nice to have
- Marketing to industrial, logistics, automotive or other operations-heavy buyers, where the decision-maker is rarely the person searching.
- Multi-market experience across India and at least one of North America, the Middle East, Southeast Asia or the UK, including local search behaviour and non-English content.
- Python, Apps Script or similar for pulling APIs and automating reports.
- Experience with AI-visibility tools (Profound, Peec, Otterly, HubSpot AI Visibility or similar) and a view on when to build versus buy.
- Conversion-rate work: landing-page tests, session recordings and heatmaps (Microsoft Clarity, Hotjar).
- YouTube and video-led demand generation.
- Digital PR or trade-media relationships in a B2B category.
Tools you'll work with
Area
Tools
Paid media
Google Ads (Search, Demand Gen, YouTube), LinkedIn Ads, Meta
Web and search analytics
GA4, Google Search Console, Microsoft Clarity
CRM and automation
HubSpot
Data and reporting
Supermetrics or similar connectors, Google Sheets, Looker Studio
SEO
Ahrefs or Semrush, Screaming Frog
AI visibility
ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews;
Prospect and intent data
ZoomInfo, Apollo
AI workflow
LLM assistants with API connectors, light Python
