cover_letter / art_oxlAykNpwH0

Dear Maven Clinic Hiring Team, Maven is doing something genuinely difficult: building a single platform that works for members at the most consequential moments of their lives — fertility, pregnancy, newborn care, menopause — while simultaneously serving the employers and health plans that fund access to it. That B2B2C tension, where member need and client pressure pull in opposite directions, is exactly the kind of product environment I have spent my career navigating. At Intuit, I owned the platform infrastructure that connected ~1.5M concurrent developer connections across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma — and the hardest part of that job was never the engineering. It was holding a principled line on what got built, for whom, and when, while enterprise partners pushed for one-off solutions that would have fragmented the platform. **Technical and Platform Foundation** My product work has always been grounded in the underlying systems. At Intuit, I delivered the ICE Self-Service platform — DevPortal, GitOps configuration, and ICE Playground — reducing developer onboarding from two to three weeks down to minutes in pre-production and under 24 hours for production, while mitigating over $1M in projected opex growth. I scaled ICE throughput from 6K to 50K TPS via an rSocket migration supporting approximately 1.5M concurrent connections with sub-25ms TP99 latency, and drove 275% year-over-year growth in ICE engagements to 675M+ in FY23. That work required deep fluency in how configuration flows through a platform — from initial setup through activation — and where it breaks under scale. The eligibility and enrollment surface at Maven is structurally similar: configuration set by employers and payers, verification logic in the middle, and member activation at the end. I know how to instrument that funnel, find where it breaks, and build the platform investments that fix it durably rather than patching it repeatedly. Beyond platform infrastructure, I have built production AI systems end to end. At Fintellect AI, I architected a RAG retrieval pipeline with ChromaDB, multi-provider LLM orchestration across Claude, GPT-4, and Gemini with fallback routing, and structured output validation. At StreamIO AI, I implemented the OpenClaw multi-agent orchestration framework with gateway protocol and subagent delegation. I raise this not because Maven's enrollment surface requires novel AI research, but because the JD specifically calls for familiarity with AI-assisted product development — and I have shipped agentic tooling in production, not just evaluated it. **Why This Role** The GPM, Client Services role at Maven sits at the exact intersection where I do my best work: long-term platform scalability on one axis, forward-deployed client partnership on the other, with a PM to develop in between. The explicit call for someone who can build a triage and prioritization framework for custom client requests — evaluate against platform leverage, sequence against core roadmap, say no when it matters — is a description of work I have done repeatedly. At Intuit, I designed a RICE-based prioritization framework across multiple microservice backlogs balancing internal partners, third-party developers, and Fortune 500 customers. At Splunk, I owned three microservice backlogs simultaneously and delivered the Scheduler Service end-to-end in approximately four months. The discipline of distinguishing what gets built from what gets routed or declined is not new to me. **Role-Specific Connection** What specifically draws me to this role is the enrollment funnel instrumentation mandate. Maven's 90-day success criteria — fully instrumented funnel, baseline metrics established, activation improvement roadmap defined — is a concrete, measurable starting point that I find compelling precisely because it is not vague. I have worked closely with telemetry and usage data in SQL and BigQuery to prioritize developer pain points across approximately 20 mobile apps and 30+ product SKUs at Intuit, and I know how to move from instrumentation to prioritized action quickly. The forward-deployed operating model — embedded with client-facing teams, present in RFP processes — also matches how I have operated; I presented at DeveloperWeek 2022 and Splunk .conf18 and .conf19, and I am comfortable owning the product relationship with external stakeholders directly. **Selected Prior Experience** - Delivered ICE Self-Service platform (DevPortal, GitOps config, ICE Playground), reducing developer onboarding from 2–3 weeks to minutes in pre-prod and under 24 hours for production, while mitigating $1M+ in projected opex growth — a direct analog to enrollment funnel optimization at scale. - Achieved 275% YoY growth in ICE engagements, scaling to 675M+ in FY23; scaled throughput from 6K to 50K TPS via rSocket migration supporting ~1.5M concurrent connections with sub-25ms TP99 — demonstrating eligibility-style platform scalability under real load. - Worked closely with telemetry and usage data (SQL, BigQuery) to prioritize developer pain points across ~20 mobile apps and 30+ product SKUs; built Asterias, a declarative asset lifecycle management platform with GraphQL API — funnel instrumentation and data-driven prioritization in a complex B2B2C environment. - Designed repeatable RICE-based prioritization framework for 3 microservice backlogs at Splunk, balancing internal partner, third-party developer, and Fortune 500 customer requirements — directly applicable to the custom client request triage framework Maven needs. - Conducted enterprise-wide Service Language Assessment across 9 languages at Intuit, analyzing usage data and developer feedback to inform strategic investment decisions presented to the CTO — experience translating complex technical tradeoffs into executive-level recommendations. - Implemented ICE Presence in async chat, generating $480K/month in additional invoicing; deployed Background-to-Foreground Messaging on iOS/Android with under 100ms latency — shipping client-facing features with measurable commercial outcomes. - Led Mailchimp GCP-to-AWS migration for MSaaS, delivering Golang template, MySQL persistence integration, and updated DevPortal documentation to meet production deadline — cross-functional execution under deadline pressure with external stakeholders. **Closing** Maven's mission — making healthcare work for all of us — is not a tagline I read past. The enrollment and eligibility surface is where that mission either reaches members or fails them quietly. A member who cannot navigate eligibility verification does not get care; a client whose configuration breaks does not renew; and a platform that bends to every one-off request eventually cannot serve anyone well. I want to build the version of this surface that holds all three of those truths at once. I would welcome the opportunity to discuss how my background maps to what Maven needs here. Sincerely, **O. Felix Amoruwa** famoruwa@berkeley.edu | 909-731-9011 | felixamoruwa.info