← alpaca / Product Manager, New Assets
tailored_resume_v2 / art_RbBa0bVc1R4
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What changed for alpaca
| change | why it matters |
|---|---|
| Fintellect AI elevated to lead experience role | Most direct proof of trading product depth — asset class selection, execution planning, risk management — which is Alpaca's core hiring signal |
| Topstep Funded Trader credential surfaced in Fintellect bullets and Additional Information | JD requires demonstrated depth on at least one trading surface; live funded trader credential is the strongest proof of genuine trading knowledge |
| Summary rewritten to lead with fintech trading platform + funded trader credential | JD's first hard requirement is trading surface depth; summary must immediately signal this before developer platform credentials |
| Intuit title reframed to 'Developer Platforms & API Infrastructure' | Mirrors JD language around API-driven products and developer experience without inflating level |
| Intuit bullets reordered to lead with 675M+ engagements / partner adoption metric | JD measures success by partner adoption and production usage — this is the strongest proof point |
| Intuit SDK bullet reframed to include 'SDK ergonomics' language | JD explicitly calls out SDK ergonomics as a success lever; candidate's experience directly matches |
| Splunk title reframed to include 'API Platform' | Alpaca is API-first; Splunk's Go microservices and SPL/SPL2 ownership maps to API contract work |
| Streamio AI moved to second position (after Fintellect) | OpenClaw multi-agent framework and AI-native workflow (Claude MCP SDK) directly address JD's AI-native PM nice-to-have; financial markets vertical is relevant |
| aeval project elevated to lead projects section | FastAPI/TimescaleDB/Redis stack and CI/CD integration most directly maps to Alpaca's API-driven, data-instrumented product culture |
| CMU MBA (Finance, Quant Analysis) elevated to lead education section | Finance concentration directly relevant to regulated trading/brokerage role; JD values finance degree |
| Bank of America bullet reframed to emphasize institutional finance and broker-dealer context | JD prefers direct broker-dealer/institutional brokerage experience; BAML Monte Carlo on $494M portfolio is the closest proof point |
| AI-native PM workflow bullet added to Additional Information | JD explicitly lists AI-native PM workflow (Claude, ChatGPT, Cursor, NotebookLM) as a nice-to-have; candidate uses Claude MCP SDK and custom agents daily |
JD analysis (17 key phrases)
Key phrases: API-driven trading capabilitiespartner adoption and production usageregulated trading executiondeveloper experiencemarket structurebroker-dealer operationscompliance, legal, and market-structure teamssequenced backlogAPI contractstrading volume, order success rate, partner activationSDK ergonomicsnew asset classancillary trading productB2B/developer-facing productsproduction cadencepartner-facing toolingAI-native PM workflow
Hard requirements:
- 5+ years PM, Engineering, Consulting, or startup experience in regulated trading/brokerage
- Demonstrated depth on at least one trading surface (MMFs, Global Stocks, FX, Options, margin, FIX, OMS)
- Experience shipping B2B/developer-facing products: SDKs, APIs, partner integrations
- Comfort shipping in parallel with compliance, legal, market-structure teams in regulated environment
- SQL and BI tool proficiency for data analysis
- Bachelor's in CS, engineering, finance, or equivalent
- Business acumen for stakeholder, tech feasibility, time, and budget tradeoffs
Preferred qualifications:
- Direct broker-dealer or institutional brokerage experience
- B2B2C correspondent/broker-as-a-service model familiarity
- Non-US trading product or complex asset class experience
- US market structure and regulatory frameworks (Reg NMS, Reg SHO, FINRA/SEC, OATS/CAT)
- FIX protocol, OMS/EMS, smart order routing, venue/liquidity-provider integrations
- Broker-dealer trading operations (exceptions, trade breaks, regulatory reporting)
- AI-native PM workflow (Cursor, Claude, ChatGPT, NotebookLM, custom agents)
Per-role mapping (7 roles scored)
| role | score | reframe angle | JD phrases that map |
|---|---|---|---|
| Fintellect AI — Founder & CEO | 5/5 | Fintech founder with direct trading product depth — asset class selection, execution planning, risk management, and AI-native workflow | new asset class, API-driven trading capabilities, partner adoption, AI-native PM workflow, regulated trading execution, developer experience |
| Intuit — Staff Product Manager | 4/5 | Enterprise-scale B2B developer platform PM — SDK ownership, API contracts, telemetry-driven prioritization, production cadence at scale | B2B/developer-facing products, SDK ergonomics, API contracts, partner adoption and production usage, production cadence, SQL, sequenced backlog |
| Splunk — Senior Product Manager | 3/5 | API-first platform PM with microservices depth, enterprise customer management, and structured prioritization frameworks | API contracts, sequenced backlog, partner-facing tooling, production cadence, B2B/developer-facing products |
| Kaiser Permanente — SOA Technical PM | 2/5 | Regulated enterprise platform PM with operational scale and infrastructure ownership | compliance, legal, and market-structure teams, partner-facing tooling, operational efficiency |
| IBM — Software Engineer | 2/5 | Engineering foundation supporting technical PM credibility | exception handling, partner-reported blockers |
| Bank of America Merrill Lynch — Tech MBA Associate | 2/5 | Institutional finance exposure with quantitative modeling | regulated trading execution, market structure, broker-dealer operations |
| Streamio AI — Founder & CEO | 3/5 | AI-native founder demonstrating custom agent workflows, API-first product delivery, and 0-to-1 execution | AI-native PM workflow, API-driven, partner-facing tooling, production cadence |
Tailored summary
Technical Product Manager with 12+ years shipping API-driven, developer-facing platforms at scale — including a fintech trading platform (Fintellect AI) covering asset class selection, execution planning, and risk management, and enterprise B2B SDK/API infrastructure serving 675M+ engagements at Intuit. Topstep-funded trader with hands-on depth in equities, macro analysis, and multi-asset execution. AI-native PM workflow: daily use of Claude, custom agents, and LLM orchestration pipelines in product discovery, PRD drafting, and prototyping. UC Berkeley Engineering + CMU MBA (Finance, Quant Analysis).