cover_letter / art_2jWNZGj0Tak

Dear NVIDIA Hardware Infrastructure Hiring Team, NVIDIA's Hardware Infrastructure organization sits at the foundation of some of the most consequential silicon development happening anywhere in the world — the platforms your team builds determine how fast engineers can design, simulate, validate, and tape out chips that power AI at global scale. That mission resonates directly with work I did at Intuit, where I owned the developer platform infrastructure serving 675M+ annual engagements across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma — and where I learned firsthand that the quality of internal tooling is a direct multiplier on engineering velocity. --- **Technical and Platform Foundation** My technical grounding spans 12+ years across software engineering, platform infrastructure, and developer-facing product management. At Intuit, I delivered the ICE Self-Service platform — a developer portal with GitOps configuration and an interactive playground — that compressed onboarding from 2–3 weeks to minutes in pre-production and under 24 hours for production, while mitigating over $1M in projected operational cost growth. I led an enterprise-wide Service Language Assessment across nine languages (Java, Python, Kotlin, Go, TypeScript, Scala, PHP, C++, Groovy), synthesizing usage telemetry and developer feedback into strategic investment recommendations presented directly to the CTO. I also built Asterias, a declarative asset lifecycle management platform with a GraphQL API, and initiated a Drift Detection and Resolution program — writing a Java JAR library to scan Git repositories for configuration drift and building a remediation roadmap using OpenRewrite. On the infrastructure side, I scaled ICE throughput from 6K to 50K transactions per second via an rSocket migration supporting approximately 1.5M concurrent connections at sub-25ms TP99 — an initiative that required close collaboration with engineering, telemetry, and platform teams across a large, distributed organization. At Splunk, I owned three interconnected microservices — Search Service (Go), Search Catalog (PostgreSQL), and Splunk Processing Language — and delivered the Scheduler Service end-to-end in roughly four months, enabling scheduled search for first-party applications. I also designed a repeatable RICE-based prioritization framework across three microservice backlogs, balancing requirements from internal partners, third-party developers, and Fortune 500 customers simultaneously. My AI/ML work adds a further layer of technical credibility: I built a full RL post-training workbench benchmarking GRPO, DPO, PPO, and nine other algorithms across TRL, VeRL, OpenRLHF, and NeMo RL frameworks, and published at NeurIPS on neural network approaches to protein structure prediction. I hold an M.S. in Software Management from Carnegie Mellon and an MBA with concentrations in Finance, Quantitative Analysis, and Economics from Tepper — the intersection of engineering depth and organizational strategy that NVIDIA identifies as a differentiator. --- **Why This Role** The through-line of my career has been building platforms that serve engineers with diverse workflows and operational models — and doing it at the scale where inconsistency becomes expensive. The NVIDIA Hardware Infrastructure PM role is a direct extension of that arc: defining product vision for internal roadmap and execution platforms, evolving them to support multiple execution models (agile, waterfall, hybrid), and driving workflow standardization without sacrificing the flexibility that different teams legitimately need. What specifically draws me to this role is the challenge of serving a user base — silicon development engineers and TPMs — whose workflows are highly specialized, deeply embedded, and resistant to change for good reason. Getting adoption right in that environment requires genuine user empathy, rigorous discovery, and the ability to translate diverse operational needs into coherent platform requirements. That is exactly the work I did at Intuit, and it is the kind of problem I find most worth solving. --- **Selected Prior Experience Most Relevant to This Role** - **ICE Self-Service Platform (Intuit):** Defined and delivered developer portal, GitOps configuration, and ICE Playground — reducing onboarding from 2–3 weeks to minutes in pre-prod and under 24 hours for production; mitigated $1M+ in projected opex growth. Directly analogous to evolving an internal platform to serve diverse engineering teams at scale. - **Enterprise Service Language Assessment (Intuit):** Conducted workflow and tooling analysis across 9 languages and ~20 mobile apps, synthesizing usage data and developer feedback into CTO-level strategic recommendations — a model for the user discovery, mapping, and analysis this role requires. - **Asterias Asset Lifecycle Management Platform (Intuit):** Built declarative platform with GraphQL API for managing developer assets across 30+ product SKUs — experience in defining internal platforms that serve multiple teams with different processes. - **MSaaS Drift Detection and Resolution (Intuit):** Initiated program to detect and remediate configuration drift across Git repositories; partnered with Design on DevPortal UI and built remediation roadmap — demonstrating workflow standardization and cross-team alignment in a complex engineering organization. - **ICE Throughput Scaling (Intuit):** Scaled from 6K to 50K TPS via rSocket migration; achieved 275% YoY growth in engagements to 675M+ in FY23 — evidence of defining success metrics, tracking adoption, and delivering measurable platform impact. - **Scheduler Service, Splunk (end-to-end delivery in ~4 months):** Owned full product lifecycle for a net-new microservice — PRD through acceptance criteria through .conf19 demo — demonstrating ability to ship internal platform capabilities on tight timelines. - **RICE Prioritization Framework, Splunk:** Designed repeatable framework across three microservice backlogs balancing internal, third-party, and enterprise customer requirements — relevant to the multi-stakeholder prioritization this role demands. - **Splunk Logging-as-a-Service, Kaiser Permanente:** Led enterprise rollout of a platform serving 200+ internal customers at 1.7 TB daily volume — early experience driving adoption of new tooling in an organization with deeply established practices. --- NVIDIA's mission to accelerate computing is realized chip by chip, and the internal platforms that govern how silicon programs are planned, tracked, and delivered are a direct lever on that outcome. I would bring to this role a track record of building exactly these kinds of platforms — at scale, across diverse engineering workflows, with measurable impact on developer velocity — and the technical depth to earn credibility with the engineers who depend on them. I would welcome the opportunity to discuss how my background maps to what the Hardware Infrastructure team is building. Sincerely, **O. Felix Amoruwa** famoruwa@berkeley.edu | 909-731-9011 | felixamoruwa.info