Role: Head of AI Search & Growth (GEO / SEO / SEM)

Function: Growth Marketing | Digital | Demand Gen

Reports to: Founders (Apex Neural)

Team scope: Build and lead a small pod (content, performance, marketing ops/analytics); scale as outcomes grow.

Why this role exists

Apex Neural is building 5060 digital ideas (products, tools, and services). We need a builder who can architect and run a unified growth engine: master the fundamentals (SEO/SEM, content, analytics) and crack the emerging frontier of GEOearning consistent inclusion and citations in AI-generated answers across major LLM/AI surfaces.

Outcomes you will own (KPIs)

- AI Answer Inclusion Rate (AAIR): % of target queries where Apex Neural (domain, brand, or asset) appears/cites in AI answers.

- LLM Citations & Mentions: Count/quality of citations and source links from AI answers and answer cards (tracked via scripted checks/manual panels).

- Non-paid pipeline: MQLs/SQLs and revenue influenced by organic (web + AI surfaces).

- SEM efficiency: CAC, ROAS, MER across Google/Bing/LinkedIn/Meta; share of spend in high-intent themes.

- Content authority & velocity: # of original research pieces/datasets published; authoritative backlinks; E-E-A-T signals.

- Technical health: Core Web Vitals, crawl/index health, structured-data coverage, index freshness (incl. IndexNow/Bing, GSC).

- Experiment throughput: # of experiments shipped/month, win rate, and time-to-learning.

What youll do

1) GEO (Generative/AI Engine Optimization)

- Define and execute the GEO strategy to earn inclusion in AI answers (ChatGPT, Gemini, Grok, Perplexity, Bing Copilot, Google AI Overviews).

- Build an LLM Inclusion Scorecard: target prompts, competitor set, weekly tracking, screenshots, and change logs.

- Create LLM-friendly assets: high-signal FAQs, How-To/Article/Guide pages, comparison tables, implementation playbooks, and concise Q&A modules aligned to real user prompts.

- Structured data & entities: Maximum JSON-LD coverage (Organization, Product/Service, Article, Author/Person, FAQ, HowTo, Breadcrumb, Video, Event). Tight author/entity pages to strengthen E-E-A-T.

- Original research & datasets: Publish benchmarks, studies, and open datasets (with clear licensing) that AI systems can safely cite.

- Open docs & APIs: Coordinate public documentation, SDK readmes, and simple endpoints that agents can reference.

- Freshness & provenance: Keep content fresh; adopt content-provenance standards (e.g., C2PA) and clear canonicalization.

- Standards watch: Track/embrace new AI crawling directives, provenance signals, and submission channels as they emerge.

2) SEO (modern, technical, durable)

- Full-funnel technical SEO with engineering: CWV performance, log-based crawl audits, sitemaps, hreflang (if needed), canonical hygiene, redirects, index management, IndexNow/Bing.

- Content architecture for 5060 ideas: scalable pillar/cluster models, internal-link maps, programmatic pages when warranted.

- Authority building: Digital PR, expert co-authorship, guest posts, and partnerships for high-quality citations.

3) SEM / Paid Growth

- Own Google/Bing/LinkedIn/Meta: account structure, SKAG/intent clusters, negatives, audiences, RSAs, sitelinks, retargeting, and budget pacing.

- Landing pages & CRO: Fast experiments on messaging, forms, social proof, and pricing; VWO/Optimizely/Equivalents for A/B tests.

4) Social & Content Engine

- LinkedIn-first B2B calendar (founder-led POVs, case studies, artifacts, demo reels), plus YouTube how-tos and Twitter/X threads.

- Content operations: briefs, outlines, editorial QA, brand voice, compliance, and repurposing (shorts, carousels, email).

5) Analytics & Ops

- GTM/Tagging discipline: GA4, GSC, Bing Webmaster, LinkedIn Insight Tag, Meta Pixel; UTM governance.

- Dashboards: Weekly growth report (AAIR, LLM mentions, SEO, SEM, pipeline, experiments).

- Attribution: Build pragmatic multi-touch views (first-touch intent + last-touch conversion).

6) Leadership

- Hire/coach a 35 person pod (performance, content, ops/analytics), and orchestrate work across 5060 initiatives after scaling initial projects.

- Drive a tight experiment cadenceproblemhypothesisMVPmeasureship learning.

What success looks like (30/60/90)

30 days

- Full audit (SEO tech/content, SEM, analytics, social).

- Baseline AAIR and LLM citations for 50 priority prompts.

- GEO Playbook v0.1 and Q3 experiment backlog.

60 days

- Ship schema coverage on top 200 pages; fix CWV for critical templates.

- Publish 2 original research pieces (with datasets).

- Launch 1015 GEO experiments; reduce waste in SEM; stand up dashboards.

90 days

- 2030% inclusion on the tracked AI prompt set (directional target; refine after baseline).

- 23 repeatable content AI citation playbooks.

- Clear pipeline lift from organic + AI-surface traffic.

Must-have experience

- 2-5 years in performance/growth marketing with deep hands-on SEO + SEM and measurable wins.

- Demonstrated AI-search/GEO work: examples of appearing in AI answers (screenshots, methodology, before/after).

- Strong technical SEO (CWV, log analysis, schema, indexation) and paid search (account design, testing, budgeting).

- Analytics fluency: GA4, GSC, Bing Webmaster, Looker Studio; comfort with funnels, cohorts, and incrementality.

- Content systems: briefing, editing, and scaling expert-led content; authority & digital PR.

- Experimentation mindset: speed to learning, rigorous measurement, and documentation.

Nice-to-have

- Basic SQL/Python for analysis; comfort with notebooks.

- Exposure to LLM tooling (embeddings, RAG-friendly docs, vector stores) and docs/API publishing.

- Experience in B2B AI/tech categories; familiarity with India & global markets.

- VWO/Optimizely (or equivalent), Screaming Frog, Ahrefs/Semrush, Similarweb; LinkedIn Ads.