cover_letter / art_V73RzBbn6Vw

Dear Airbnb Hiring Team, Airbnb has done something genuinely rare: built a global marketplace that doesn't just move inventory but changes how people experience the world. The homepage and discovery surface is where that promise either lands or doesn't — it's the moment a guest decides whether to keep scrolling or book a trip that becomes a story they tell for years. That intersection of AI-powered relevance, consumer delight, and marketplace economics is exactly where I've spent the last several years of my career, and it's why this role caught my attention immediately. **Technical and AI Foundation** My product work is grounded in hands-on technical depth that I've built continuously — from a NeurIPS-published neural network for protein structure prediction (originally hand-coded in C++ with custom backpropagation through time in 2004, rewritten in 2026 as a full PyTorch platform spanning 413 to 8B parameters) to a production RL post-training workbench I built this year that benchmarks GRPO, DPO, and 10 other algorithms across TRL, VeRL, OpenRLHF, and NeMo RL. I also built aeval, a local-first model evaluation platform with statistical rigor — bootstrap confidence intervals, Welch's t-test, Cohen's d — and CI/CD safety gates. I bring this background not because every PM role requires it, but because building AI-powered discovery and relevance systems at Airbnb's scale demands a PM who can credibly partner with ML engineers on ranking models, personalization architectures, and evaluation frameworks — not just translate requirements. On the consumer platform side, I spent three years at Intuit as a Staff PM owning developer-facing infrastructure that scaled to 675M+ engagements in FY23 across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma. I drove 275% YoY growth in ICE engagements and scaled throughput from 6K to 50K TPS via an rSocket migration supporting approximately 1.5M concurrent connections at sub-25ms TP99. That work required the same muscle Airbnb needs here: translating user pain points into platform investments, aligning engineering and design around a shared roadmap, and measuring impact with precision. **Why This Role** My career arc has moved from enterprise infrastructure toward consumer-facing AI products — and this role sits at exactly that intersection. As a founder, I've shipped 0-to-1 AI products end-to-end, including an RAG retrieval pipeline with multi-provider LLM orchestration and a multi-agent framework with subagent delegation. As a platform PM, I've owned the full lifecycle from roadmap to executive alignment to shipped product at scale. The Airbnb Homepage PM role asks for both: the strategic vision to reimagine discovery across Homes, Services, Experiences, and emerging verticals, and the hands-on execution to ship it. **What Excites Me About This Specific Role** Airbnb's homepage is one of the highest-leverage surfaces in consumer tech — a single scroll that needs to serve a solo traveler looking for a shared room, a family planning a Luxe escape, and an international guest discovering Experiences for the first time. The opportunity to incorporate AI-powered relevance models and new browsing formats into that surface, while coordinating across marketing lifecycle campaigns and new business verticals like Hotels and Partnerships, is a genuinely complex product problem. I'm particularly drawn to the challenge of building discovery that works globally — where personalization must account for cultural context, language, and market maturity — and to the mandate of defining measurable OKRs that connect browsing behavior to bookings growth. **Selected Prior Experience** - **675M+ platform engagements at Intuit (FY23):** Drove 275% YoY growth in ICE engagements across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma — a direct analog to scaling discovery impact across Airbnb's multi-vertical marketplace. - **ICE Self-Service Platform:** Delivered DevPortal, GitOps config, and ICE Playground, reducing developer onboarding from 2–3 weeks to minutes — demonstrating ability to ship complex platform products with measurable time-to-value outcomes. - **Fintellect AI RAG Pipeline:** Architected retrieval pipeline with ChromaDB vector store, multi-provider LLM orchestration (Claude, GPT-4, Gemini) with fallback routing, structured output validation, and token budget optimization — directly applicable to building AI-powered relevance and personalization layers for homepage discovery. - **OpenClaw Multi-Agent Orchestration (StreamIO):** Implemented multi-agent framework with gateway protocol, subagent delegation, and session management across real estate, financial markets, and insurance verticals — experience building AI systems that coordinate across distinct product domains, analogous to Airbnb's multi-vertical discovery challenge. - **Splunk Scheduler Service (0-to-1 in ~4 months):** Delivered end-to-end scheduled search capability from concept to .conf19 demo in approximately four months — evidence of the fast-paced, hands-on execution the JD explicitly calls for. - **RICE Prioritization Framework at Splunk:** Designed repeatable RICE-based prioritization across three microservice backlogs, balancing internal partner, third-party developer, and Fortune 500 customer requirements — the same cross-functional alignment muscle needed to sequence discovery investments across Homes, Experiences, Hotels, and Luxe. - **Telemetry-Driven Prioritization at Intuit:** Used SQL and BigQuery to prioritize developer pain points across ~20 mobile apps and 30+ product SKUs, building data-backed cases for platform investment — directly maps to Airbnb's expectation of using marketplace data and user research to drive discovery strategy. **Closing** Airbnb's mission — to create a world where anyone can belong anywhere — lives or dies on discovery. A guest who can't find the right stay doesn't belong anywhere on the platform. I want to build the homepage that changes that: one that uses AI not as a feature but as the underlying intelligence that makes every guest feel like the product was built for them. I'd welcome the opportunity to discuss how my background in AI product development, platform-scale execution, and consumer marketplace thinking maps to what you're building. Thank you for your time and consideration. Sincerely, **O. Felix Amoruwa** famoruwa@berkeley.edu | 909-731-9011 | felixamoruwa.info