Your Positioning — Elevator Pitch
3 points
The 30-Second Version
Must Use
"I'm an SEO and digital marketing specialist with 7 years of experience, currently managing search strategy across 8 life sciences brands in the US and UAE/GCC markets. I've been actively transitioning my practice from traditional SEO into GEO and AEO — I see AI-driven search as the inevitable future, not a side project. I'm looking for a role where that's the entire mission, not something I'm bolting onto an existing job."
Why Indegene Specifically
Must Use
- Indegene is building a GEO practice inside a company that already has deep pharma credibility with 20 of the top 20 biopharma companies
- That combination — GEO expertise + pharma domain — is extremely rare, and it sits exactly where your experience is heading
- You want to be part of defining the methodology, not inheriting someone else's playbook
- The role is a senior IC + advisory position — you want to shape strategy, not just execute tickets
Your Unique Angle
Strong Point
"Most people in GEO come from pure SEO or pure AI. I come from managing SEO across 8 life sciences brands simultaneously — reproductive health, stem cell banking, fertility clinics, biotech. I already live in the YMYL, E-E-A-T, medically-sensitive content world. Adding GEO methodology on top of that foundation is a natural evolution, not a pivot."
AI & GEO Tactics — The Heavy Section
8 areas
Entity Optimization & Knowledge Graph Strategy
Must Use
- Build and reinforce brand entities so LLMs recognize them as distinct, authoritative sources — not just keywords on a page, but structured knowledge
- Google Knowledge Panel optimization — claiming, enriching, and maintaining brand panels with verified information
- Wikidata and Wikipedia presence strategy (where appropriate) — LLMs pull heavily from these structured data sources during inference
- Consistent NAP + entity data across all structured sources (Google Business Profile, Bing Places, industry directories, medical registries)
- Linking brand entities to broader knowledge graph concepts — therapeutic areas, medical conditions, treatment categories — so LLMs associate the brand with the right clinical context
- Cross-platform entity consistency — ensuring the brand identity is uniform across Google, Bing, Apple, and LLM-accessible databases
💡 Why This Matters for Pharma
When a patient asks ChatGPT "What are the best IVF clinics in San Diego?", the LLM constructs its answer from entity knowledge. If your client's brand isn't a well-defined entity with clear associations, it simply won't appear.
Schema.org Structured Data for AI Readability
Must Use
- Implementing JSON-LD markup beyond the basics —
MedicalCondition,Drug,MedicalProcedure,FAQPage,HowTo,Organization,Person(for physician/expert bios) - Speakable schema for voice search and AI assistants — marks content sections as ideal for text-to-speech extraction
- Structured data for medical content that helps LLMs understand clinical context (indications, dosage forms, treatment protocols)
- Schema validation workflow: Google Rich Results Test → Schema.org Validator → Screaming Frog structured data audit → fix → re-crawl
- Event and LocalBusiness schema for clinic locations, physician directories, and patient-facing service pages
💡 Talk Track
"Schema is the bridge between human-readable content and machine-readable knowledge. For pharma, it's especially critical because LLMs need to understand the clinical precision of what you're describing — a Drug schema tells the AI this is a specific pharmaceutical product with indications and contraindications, not just a page with keywords."
AI-First Content Architecture
Must Use
- Restructuring content into clear, concise, "quotable" blocks — LLMs favor content with direct definitions, clear Q&A pairs, and structured data
- Writing for AI extraction: leading paragraphs that directly answer the query, followed by supporting detail — inverted pyramid optimized for LLM citation
- Conversational keyword research — mapping how people query LLMs (natural language, full questions, multi-turn conversations) vs. traditional short-tail keyword fragments
- Topic clustering and pillar-page architecture that builds topical authority — LLMs favor sources that comprehensively cover a subject
- FAQ optimization with conversational, long-tail queries that mirror how users prompt AI — "What should I ask my doctor about IVF?" vs. "IVF questions"
- Content freshness signals — regular updates, visible timestamps, "last reviewed by [MD/PharmD]" markers that signal recency to both search engines and LLMs
- Definitive statement formatting — LLMs prefer content that makes clear, authoritative claims over hedging language. Structure content with confident, factual lead sentences.
💡 The Shift
Traditional SEO optimizes for click-through. GEO content architecture optimizes for citation and extraction — your content needs to be the source an AI quotes, not just the page a user visits.
E-E-A-T Signal Strengthening (Critical for Pharma/YMYL)
Must Use
- Author bio optimization with verifiable credentials (MDs, PhDs, PharmDs) — LLMs weight expert authorship heavily in health/medical topics
- Expert review and medical review attribution on all clinical content — "Reviewed by Dr. [Name], Board-Certified [Specialty]"
- Source citation and reference linking — making content cite-worthy by including original data, clinical studies, and expert quotes with proper attribution
- Building authority through backlinks from high-trust medical/scientific domains (.edu, .gov, NIH, peer-reviewed journals, medical associations)
- Byline consistency across the web — same expert entities publishing across multiple authoritative platforms reinforces their knowledge graph identity
- First-hand experience signals — patient testimonials (compliant), clinical case studies, procedure walkthroughs that demonstrate real Experience in E-E-A-T
💡 Pharma-Specific Angle
"In pharma YMYL content, E-E-A-T isn't optional — it's the foundation. LLMs are increasingly cautious about health misinformation, so they over-index on authoritative sources. If your content doesn't clearly signal medical expertise and editorial rigor, AI platforms will cite your competitor's content instead."
Prompt Testing & AI Visibility Monitoring
Must Use
- Systematic prompt testing across ChatGPT, Perplexity, Google Gemini, Bing Copilot, and Claude — querying brand names, therapy areas, competitor comparisons, patient/HCP questions
- Documenting how each LLM surfaces or ignores brand content — citation patterns, source attribution accuracy, content hallucination risks
- Tracking AI Overviews in Google SERPs — which queries trigger them, whether client content is cited, and how competitors are positioned
- Perplexity source tracking — Perplexity explicitly cites sources with links, making it the most transparent platform for measuring AI citation performance
- Prompt variation testing — same topic, different phrasings, different user personas (patient vs. HCP vs. caregiver) — to understand how content structure affects LLM responses
- Competitive AI share of voice analysis — running identical prompts for competitors to benchmark visibility across platforms
- Longitudinal tracking — running the same prompts weekly/monthly to detect changes in LLM behavior and citation patterns over time
💡 Talk Track
"I've been doing this for the brands I manage — testing how our fertility clinics and stem cell banking brands show up when patients ask ChatGPT or Perplexity questions about treatments. The insights are immediate: you can see exactly where your content is being cited, where it's being ignored, and where competitors are winning."
LLM Content Attribution & Discoverability
Strong Point
- Optimizing content to be "citable" — clear, factual, well-sourced content that LLMs prefer to reference when generating answers
- Brand mention seeding in high-authority third-party content (industry publications, medical journals, news outlets) — LLMs train on and retrieve from these sources
- Digital PR strategy focused on authoritative publications that feed LLM training data and retrieval indexes
- Ensuring content isn't blocked by robots.txt or paywalls that prevent LLM crawling — balancing content access vs. protection (critical strategic decision for pharma)
- Crawl budget optimization specifically for AI crawlers (GPTBot, Google-Extended, ClaudeBot, PerplexityBot) — monitoring which AI bots are accessing your content and ensuring they can reach high-value pages
- robots.txt strategy for AI: Deciding which AI crawlers to allow/block is a strategic choice — you need to balance brand visibility in AI platforms against content scraping concerns
Semantic SEO & Topical Authority
Strong Point
- Building semantic content maps that cover entire topic clusters — LLMs reward depth and breadth of coverage on a subject
- Internal linking architecture that reinforces topical relationships and entity connections — signals to both search engines and LLMs that your site is a comprehensive authority
- Content gap analysis using AI tools — identifying topics where competitors are cited by LLMs but you're absent
- NLP analysis of existing content to align with how LLMs parse and understand text — optimizing for semantic similarity to likely user queries
- Co-occurrence optimization — ensuring related entities, terms, and concepts appear together naturally, reinforcing topical relevance for AI interpretation
AI-Powered Content Optimization Workflow
Good to Mention
- Using AI tools (ChatGPT, Claude, Gemini) in the content creation workflow — drafting, refining, and testing content for AI readability before publishing
- AI-assisted content audits — running existing content through LLMs to test comprehension, factual accuracy, and citation potential
- Automated monitoring workflows for tracking brand mentions across AI platforms — alerts when citation patterns change
- Using AI to generate Schema markup and structured data — then validating and refining for accuracy
- Prompt engineering for content briefs — using LLMs to research what information users actually want, then structuring content to answer those needs
⚠️ Pharma Caveat
Always flag that AI-generated content in pharma must go through MLR (Medical, Legal, Regulatory) review. You're using AI as a tool in the workflow, not as the final publisher. This shows you understand the compliance reality.
AI & SEO Tool Stack
13 tools
Your Complete Tool Stack (Mapped to JD)
Strong Point
| Tool | Category | How You Use It for GEO |
|---|---|---|
| ChatGPT | AI Platform | Prompt testing for brand visibility, content drafting/optimization, competitive monitoring, AI citation testing |
| Perplexity | AI Platform | Citation tracking (most transparent source attribution), competitive AI share of voice, content discoverability testing |
| Google AI Overviews | AI Platform | SERP monitoring for AI Overview triggers, AEO optimization, tracking which content gets featured |
| Google Gemini | AI Platform | Prompt testing, content comprehension testing, alternative LLM perspective on brand visibility |
| Bing Copilot | AI Platform | Microsoft ecosystem visibility testing, enterprise search behavior, prompt testing |
| Claude | AI Platform | Content testing, long-form analysis, alternative citation behavior (different training data than GPT) |
| Semrush | SEO | Keyword research, competitive analysis, site audits, position tracking, backlink analysis, content gap analysis |
| Ahrefs | SEO | Backlink analysis, content gap analysis, entity/authority research, competitor backlink profiling |
| Screaming Frog | Technical | Technical SEO audits, structured data validation, crawl analysis, Schema extraction and verification |
| Google Analytics 4 | Analytics | Traffic analysis, conversion tracking, AI-referred traffic segmentation, user behavior analysis |
| Google Search Console | Analytics | Performance monitoring, indexing status, click/impression data, AI Overview appearance tracking, crawl stats |
| Schema.org Validator | Technical | Structured data testing and validation, ensuring JSON-LD accuracy before deployment |
| Rich Results Test | Technical | Schema markup testing for rich snippet eligibility, preview rendering verification |
💡 JD Tools You Don't Have Yet
Profound (pharma-specific search intelligence), BrightEdge, Conductor, Looker Studio — if asked, say: "I haven't used Profound or BrightEdge yet, but I'm a fast learner on SEO tooling — the strategic thinking transfers, the UI is just a learning curve." Don't volunteer the gap; only address if asked.
AI Metrics & KPIs You'd Build
5 KPIs
The 5 GEO KPIs (Named in the JD)
Must Use
These are the exact metrics the JD calls out. You need to speak to each one fluently:
AI Citation Rate
How often brand content is cited by LLMs when users query relevant topics. Measured through systematic prompt testing across platforms and Perplexity source tracking.
Entity Authority Score
Strength of brand's knowledge graph presence — Knowledge Panel completeness, Wikidata presence, structured data coverage, cross-platform entity consistency.
LLM Content Coverage
What percentage of key topics, products, and therapies are represented in LLM outputs. Gap analysis by topic cluster against target keyword universe.
AI Share of Voice
Brand presence in AI-generated answers vs. competitors for key therapeutic and brand queries. Benchmarked monthly across all major AI platforms.
AI Overview Appearance
How often client content appears in Google AI Overviews for target queries. Tracked via Search Console and manual SERP monitoring.
How You'd Build the Measurement Framework
Strong Point
"I haven't built a formal AI metrics dashboard yet — that's one of the reasons this role excites me. But I know exactly what needs to be measured and how to build the framework. I've been doing the tactical work — prompt testing, content restructuring, Schema implementation — and I'm ready to operationalize that into a repeatable measurement practice at scale."
Framework Approach
- Define the prompt library: Build a standardized set of prompts per brand/therapy area that map to business-critical queries (patient questions, HCP queries, competitive comparisons)
- Establish baselines: Run all prompts across ChatGPT, Perplexity, Gemini, Copilot, Claude — document current citation rates, share of voice, and content coverage
- Build the tracking cadence: Weekly prompt testing with monthly reporting — track changes over time, correlate with content optimization efforts
- Create the dashboard: Aggregate metrics into a client-facing dashboard showing AI visibility trends alongside traditional SEO metrics — GA4 + Search Console + AI KPIs
- Competitive benchmarking: Run the same prompts for top 3-5 competitors — report AI share of voice as a competitive metric
Life Sciences & Pharma Positioning
4 points
CSG.BIO as Life Sciences Experience
Must Use
- You manage SEO/AI strategy across 8 brands in reproductive health, stem cell banking, fertility, and biotech — this IS life sciences
- You work across two markets (US and UAE/GCC), giving you international SEO and multi-regulatory experience
- Your brands include fertility clinics (Hanabusa IVF, NEFI), stem cell banking (AlphaCord, CellSave), and patient-facing DTC services (CryoChoice) — covering both HCP and patient audiences
- You navigate multiple CMS platforms (Shopify, Webflow, Strapi, HubSpot) and multiple CRM/marketing stacks (HubSpot, Salesforce, Klaviyo, Zoho) — enterprise-level complexity
- You coordinate with three external agencies (Hawke Media, Hypefeed, Talir) across PPC, SEO, and social — this IS matrixed stakeholder management
Pharma-Adjacent Parallels
Strong Point
- Reproductive health content is YMYL (Your Money Your Life) — same content sensitivity and E-E-A-T requirements as pharma
- Fertility treatments involve patient education, clinical content, and regulatory considerations — parallel to pharma HCP/DTC marketing
- Stem cell banking requires trust-building, scientific credibility, and expert authority — the same content authority principles pharma GEO demands
- UAE/GCC market experience means you've worked with region-specific regulatory frameworks — analogous to navigating FDA/EMA/CDSCO differences
"I've been doing life sciences SEO at the brand level across multiple therapeutic areas and markets — I'm ready to do it at the consulting level for enterprise pharma clients."
MLR / MedLegal Awareness
Good to Mention
- The JD heavily emphasizes navigating MLR (Medical, Legal, Regulatory) review — show you understand this is a constraint that shapes every GEO recommendation
- AI platforms may surface content in ways that lack proper fair balance, ISI (Important Safety Information), or required disclaimers — creating compliance risk that traditional SEO never had
- The tension between maximizing AI discoverability while staying regulatory-compliant is probably the single hardest part of this role — and the biggest value-add for clients
- You can speak to this from experience: fertility and stem cell content has its own compliance requirements around medical claims
💡 If They Ask About MLR Specifically
Be honest that you haven't worked in a formal pharma MLR review process, but emphasize that you've managed medically-sensitive content that requires accuracy, proper disclaimers, and expert review. The principle transfers; the specific process is learnable.
Multi-Brand Strategy = Consulting Mindset
Strong Point
- Managing SEO across 8 brands simultaneously is fundamentally a consulting skillset — each brand has different markets, competitors, audiences, and business models
- You've prioritized, roadmapped, and sequenced work across competing brand priorities — that's engagement management
- You're doing the same work a consulting firm would do, just internally — the transition to client-facing advisory is a natural evolution, not a career change
Leadership & Consulting Credibility
3 points
CEO Reporting & Executive Communication
Must Use
"I reported directly to the CEO of a global holding company on a weekly basis — presenting SEO performance metrics, strategic recommendations, and competitive intelligence across our entire brand portfolio."
What This Demonstrates
- Executive communication: You can translate data into business narratives for C-suite audiences
- Data-driven storytelling: Weekly metrics presentations require distilling complex SEO data into actionable insights
- Strategic thinking: You weren't just executing — you were advising leadership on direction
- Comfort with senior stakeholders: The JD requires "client-facing credibility at the VP/Director level" — you've operated at the CEO level
💡 Emphasize
You were the SEO/AI decision-maker across all 8 brands — not one of many specialists, but the strategist setting direction for the entire portfolio.
Agency Coordination as Matrixed Work
Strong Point
- Managing relationships with Hawke Media, Hypefeed, and Talir means you're already operating in a matrixed environment
- You coordinate with external teams, align on strategy, and review deliverables — this mirrors the Indegene model of working with account teams, delivery squads, and capability leads
- Different agencies for different brands means you've managed multiple vendor relationships simultaneously — each with different approaches and capabilities
Certifications
Good to Mention
- Technical SEO Certification — demonstrates depth beyond content strategy into crawlability, indexing, site architecture, structured data
- SEO Manager Certification — validates strategic and managerial capability, not just execution
- The JD lists certifications from Google, BrightEdge, Moz, HubSpot, Semrush, Profound as "an advantage" — your certs show commitment to professional development
Addressing Gaps — Honest Framing
4 gaps
Low Risk
7 Years vs. 8+ Required
▼
Medium
No MBA
▼
Medium
No Formal AI Metrics Dashboard
▼
Low Risk
Pharma vs. Life Sciences
▼
Questions to Ask the Hiring Manager
8 questions
1
"How mature is the GEO practice today — am I joining a team with established methodology, or helping build it from scratch?"
Shows you read the JD and understand the stage. Also helps you gauge if this is a real practice or a pitch deck.
2
"What does a typical GEO engagement look like end-to-end? What's the average engagement length and team composition?"
Shows consulting mindset. Tells you about deal size, team structure, and your day-to-day reality.
3
"How are you currently measuring AI citation rate and AI share of voice for clients? Is there an internal tool, or is that part of what this role would build?"
Shows you understand the metrics the JD names. Also reveals how far along their tooling actually is.
4
"How do MLR/MedLegal review processes typically interact with GEO recommendations? Is there friction, or have clients figured out a workflow?"
Shows pharma regulatory awareness. This is one of the hardest problems in pharma GEO — asking about it signals domain sophistication.
5
"What's the split between strategy development and client-facing delivery in this role? How much time is spent in front of clients vs. building internal IP?"
Practical question about day-to-day. Tells you if this is a client-facing advisory role or more internal methodology building.
6
"Where are you seeing the most client demand right now — specific therapeutic areas, brand vs. corporate, HCP vs. patient audiences?"
Shows market thinking. The answer tells you where the real revenue is and what you'd work on first.
7
"How does GEO fit into Indegene's broader omnichannel and content strategy offering? Is it a standalone practice or integrated into existing client engagements?"
Shows you're thinking about how GEO connects to their existing business, not just your silo. Strategic consultants think in portfolios.
8
"What does success look like for this role in the first 6 months? What would make you say 'this was the right hire'?"
Classic closer. Gets the hiring manager to verbalize their expectations, which you can then reference in follow-up emails.