cover_letter / art_8ofdzkvdLic

Dear Alpaca Hiring Team, Alpaca is building the infrastructure layer that makes regulated trading accessible to developers and financial institutions worldwide — a genuinely hard problem that sits at the intersection of market structure, compliance, and developer experience. That combination is precisely where I have spent the last several years: first as a funded trader (Topstep) who has lived inside order execution and position management, and most recently building AI-powered financial education and investing tools at Fintellect AI, where I architected RAG retrieval pipelines, multi-provider LLM orchestration, and domain-specific conversational agents scoped to distinct financial focal points for retail investors. **Technical and Product Foundation** My product and engineering background spans both sides of the stack this role demands. At Intuit, I owned developer-facing platform infrastructure at genuine scale — extending Java and Python SDK Starter Kits with scaffolding templates, CI/CD integration, and build configurations, while delivering the ICE Self-Service platform that reduced developer onboarding from two to three weeks down to minutes in pre-production and under 24 hours for production. That platform scaled to 675M+ engagements in FY23 across QuickBooks, TurboTax, Mint, Mailchimp, and Credit Karma, with throughput growing from 6K to 50K TPS via an rSocket migration supporting approximately 1.5M concurrent connections at sub-25ms TP99. I know what it takes to ship APIs that developers actually adopt — not just ship dates, but activation, integration ergonomics, and the operational instrumentation to know when something is blocking a partner. At Splunk, I owned Search Service (Go microservices), Search Catalog (PostgreSQL metadata service), and Splunk Processing Language — building product roadmaps, PRDs, and acceptance criteria while shipping the Scheduler Service end-to-end in roughly four months and driving up to 10x query performance improvements for a beta enterprise customer. I am comfortable working with SQL and BigQuery to surface developer pain points, and I have built RICE-based prioritization frameworks to balance internal partner, third-party developer, and Fortune 500 customer requirements simultaneously. On the financial side, my Fintellect AI work included building AI-powered charting and macroeconomic analysis tools for asset class selection, execution planning, and risk management — integrated with LLM models for automated trade analysis. I hold a Carnegie Mellon MBA with concentrations in Finance, Quantitative Analysis, and Economics, and a UC Berkeley BS in Computational Engineering Science, which gives me the technical depth to engage credibly with market structure and execution teams and the financial fluency to reason about trading product tradeoffs. **Why This Role** The PM, New Assets role is a direct match for the kind of work I find most substantive: owning a regulated trading sub-surface end-to-end, shipping API-driven capabilities to developers and institutional partners, and measuring success by production adoption rather than documentation volume. Alpaca's B2B2C correspondent model — where partners are the primary customer and retail accounts are downstream — mirrors the developer-platform dynamic I navigated at Intuit, where the internal developer was the customer and the end consumer was several layers removed. What specifically draws me to this role is the combination of asset class depth and developer experience. Whether the surface is Money Market Funds, Global Stocks, FX, or Options, the challenge is the same: translate complex market structure and regulatory constraints into clean API contracts that partners can implement against, then track adoption metrics — trading volume, order success rate, partner activation — and iterate until the surface is genuinely being used. That feedback loop is exactly how I operated at Intuit with ICE engagement metrics and at Splunk with search performance benchmarking. **Selected Relevant Experience** - **Fintellect AI:** Architected RAG retrieval pipeline with ChromaDB vector store, multi-provider LLM orchestration (Claude, GPT-4, Gemini) with fallback routing, and built AI-powered charting and macroeconomic analysis tools for asset class selection, execution planning, and risk management — serving retail investors through a mobile-first platform launched on the App Store. - **Intuit — SDK and Developer Platform:** Extended Java and Python SDK Starter Kits with scaffolding, build configurations (Gradle/Maven), testing frameworks, and CI/CD integration; delivered ICE Self-Service DevPortal reducing onboarding from weeks to minutes while mitigating $1M+ in projected opex growth. - **Intuit — Scale and Telemetry:** Scaled ICE to 675M+ engagements in FY23; used SQL and 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. - **Splunk — Search Orchestration:** Owned Go microservice roadmaps and PRDs for Search Service, Search Catalog, and SPL/SPL2; shipped Scheduler Service end-to-end in ~4 months; achieved up to 10x query performance improvement for a beta enterprise customer through benchmark-driven optimization. - **Splunk — Prioritization Framework:** Designed repeatable RICE-based prioritization framework across 3 microservice backlogs, balancing internal partner, third-party developer, and Fortune 500 customer requirements — directly analogous to the compliance/legal/engineering alignment this role requires. - **Kaiser Permanente — Platform Operations:** Led enterprise rollout of Splunk Logging-as-a-Service (1.7 TB daily volume, 200+ internal enterprise customers) and built Redis-based caching capability addressing scalability, fault tolerance, and data redundancy — experience directly relevant to exception handling and operational automation in a regulated environment. - **Topstep Funded Trader:** Active funded trader with direct experience in order execution, position management, and the practical realities of trading infrastructure from the practitioner side. **Closing** Alpaca's mission — opening financial services to everyone on the planet — is meaningful precisely because the infrastructure problem is hard. Regulated trading APIs that developers can actually build on, across asset classes and geographies, require someone who can hold market structure complexity and developer experience in the same frame simultaneously. That is the work I have been doing, and I would welcome the opportunity to bring it to Alpaca's platform. Thank you for your consideration. --- **O. Felix Amoruwa** famoruwa@berkeley.edu | 909-731-9011 | felixamoruwa.info