← robinhood / Staff Product Manager, Cortex
tailored_resume_v2 / art_YiJByvC4CDA
role
model
anthropic/claude-sonnet-4.6
created
2026-05-20T22:13
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What changed for robinhood
| change | why it matters |
|---|---|
| Fintellect AI moved to lead experience role, above Streamio AI | Direct analog to Cortex — consumer-facing AI financial platform with RAG, multi-LLM orchestration, and domain-specific financial agents maps precisely to the role's core mission |
| Fintellect AI bullets reframed around RAG pipeline, conversational AI agents, and personalized financial guidance | JD's top requirements are LLM architectures, agentic systems, RAG, and consumer-facing financial AI — these are the strongest proof points |
| Streamio AI bullets condensed to 3, leading with OpenClaw multi-agent orchestration | Agentic AI systems in production is a preferred qualification; streaming/media details deprioritized |
| Intuit title reframed to 'Consumer Platform & Developer Infrastructure' | Emphasizes consumer scale (675M+ engagements) over internal developer tooling to match Cortex's consumer focus |
| Intuit lead bullet is 675M+ engagements / scale metric | JD implies success metrics around adoption and retention at scale; enterprise proof point belongs first |
| aeval project moved to lead the projects section | JD explicitly requires 'evaluation frameworks that measure AI quality, accuracy, and safety at scale' — aeval is the strongest direct proof point |
| Summary rewritten to lead with consumer AI financial platform credential and RAG/agentic fluency | JD's first sentence defines Cortex as consumer-facing AI for financial life; summary must mirror this identity immediately |
| RL Workbench reframed to emphasize benchmarking and model strategy decisions | Maps to JD's 'model strategy' and 'evaluation frameworks' requirements; Arena/Reward Lab are evaluation infrastructure |
| Bank of America bullet reframed to emphasize quantitative financial analysis in investment banking context | JD prefers background in financial advice, portfolio management, or wealth-tech; this is the only direct financial services experience from earlier career |
| Kaiser Permanente bullets condensed to 2, leading with regulated industry delivery | JD requires experience shipping AI products in regulated industries; healthcare regulated environment is relevant signal |
| IBM condensed to 1 bullet | Lowest relevance role; space optimization while preserving role continuity |
JD analysis (20 key phrases)
Key phrases: consumer-facing AIagentic systemsretrieval-augmented generationevaluation frameworksAI quality, accuracy, and safety at scaleLLM architecturesmodel strategypersonalized financial guidancedemocratize financeship with confidence and improve continuouslyregulatory landscapeconversational experienceAI architecturefrontier of what's possiblefinancial planning and adviceportfolio managementwealth-techagentic AI systems in productionLLM evaluation and observabilityconsumer intuition
Hard requirements:
- 7+ years consumer-facing product management
- 3+ years AI/ML-powered products
- Deep fluency in LLM architectures, agentic systems, RAG
- Build-vs-buy decisions, model selection, system design
- Evaluation frameworks for AI quality, accuracy, safety at scale
- Consumer-obsessed AI product craft
- Cross-functional execution across engineering, design, data science, compliance
- Comfort operating in ambiguity
Preferred qualifications:
- Experience shipping AI products in financial services or regulated industries
- Familiarity with LLM evaluation and observability tooling
- Experience with agentic AI systems in production
- Background in financial advice, portfolio management, or wealth-tech products
Per-role mapping (9 roles scored)
| role | score | reframe angle | JD phrases that map |
|---|---|---|---|
| Fintellect AI — Founder & CEO | 5/5 | Consumer-facing AI financial product with RAG, multi-LLM orchestration, and agentic advisory — direct analog to Cortex | consumer-facing AI, retrieval-augmented generation, agentic systems, personalized financial guidance, financial planning and advice, portfolio management, wealth-tech, LLM architectures |
| Streamio AI — Founder & CEO | 3/5 | Agentic AI systems in production; multi-agent orchestration architecture | agentic systems, agentic AI systems in production, model strategy |
| Intuit — Staff Product Manager | 4/5 | Consumer AI platform at massive scale with cross-functional leadership and data-driven prioritization | consumer-facing, ship with confidence, cross-functional execution, adoption and retention |
| Splunk — Senior Product Manager | 3/5 | Data platform and search orchestration with performance optimization and structured prioritization | system design, AI quality, accuracy, and safety at scale |
| Kaiser Permanente — SOA Technical PM | 2/5 | Regulated industry platform delivery | regulatory landscape, regulated industries |
| IBM — Software Engineer | 1/5 | Engineering foundation | — |
| Bank of America Merrill Lynch — Tech MBA Associate | 2/5 | Financial services and quantitative investment background | portfolio management, financial planning and advice |
| RL Workbench — Post-Training RL Platform | 4/5 | AI evaluation and benchmarking infrastructure — maps directly to Cortex evaluation frameworks requirement | evaluation frameworks, AI quality, accuracy, and safety at scale, ship with confidence and improve continuously, model strategy, frontier of what's possible |
| aeval — AI Model Evaluation Platform | 5/5 | Purpose-built LLM evaluation and observability platform — directly addresses JD's evaluation frameworks requirement | evaluation frameworks, AI quality, accuracy, and safety at scale, LLM evaluation and observability tooling, ship with confidence and improve continuously, automated quality, accuracy, and safety measurement systems |
Tailored summary
Consumer AI product leader with 12+ years building AI-powered products at scale — from shipping a RAG-orchestrated, multi-LLM financial advisory platform for retail investors (Fintellect AI) to scaling Intuit's consumer platform to 675M+ engagements. Deep technical fluency in LLM architectures, agentic systems, and retrieval-augmented generation, with hands-on experience building evaluation frameworks that measure AI quality, accuracy, and safety at scale. NeurIPS published researcher; track record of translating frontier AI research into shipped consumer products in financial services and regulated environments.