← databricks / Staff Product Manager, Agentic AI Applications
tailored_resume_v2 / art_6XN3Nd2R1fM
role
model
anthropic/claude-sonnet-4.6
created
2026-06-26T19:59
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What changed for databricks
| change | why it matters |
|---|---|
| Summary rewritten to lead with agentic platform and MCP connector experience, embedding 'managed agent runtime,' 'MCP connectors,' 'model gateway abstraction,' 'governed tool invocation,' and 'time-to-production' | JD's first requirement is owning the Agentic Platform strategy; summary must immediately signal agent runtime and MCP fluency |
| Streamio AI title reframed to 'Agentic Platform & Developer Tooling' and OpenClaw bullet rewritten to foreground 'managed agent runtime,' 'multi-step orchestration,' and 'governed tool invocation' | OpenClaw is the strongest direct proof point for the JD's agent runtime requirement; must lead the role |
| MCP SDK bullet elevated to second position in Streamio AI role | JD explicitly calls out MCP (Model Context Protocol) as a preferred qualification and core platform component; direct experience must be surfaced immediately |
| Fintellect AI reframed around 'RAG intelligence layer,' 'model gateway abstraction,' and 'domain-specific agents' language | JD's intelligence layer section maps directly to RAG + multi-provider LLM orchestration; framing must mirror JD's three-layer architecture language |
| Intuit role reordered: 675M+ engagements / 50K TPS bullet moved to first position; ICE Self-Service 'self-service by construction' bullet second | JD values enterprise-grade scale and self-service developer platforms; strongest proof points must lead |
| Intuit Drift Detection bullet reframed as 'platform governance and gold-standard promotion pipeline analog' | JD explicitly calls for a gold-standard promotion pipeline from prototype to production; governance tooling maps directly |
| aeval project moved to lead the Projects section | JD's evaluation framework section is one of the six core platform pillars; aeval is the strongest direct proof point with LLM-as-judge analog, CI/CD safety gates, and automated quality scoring |
| aeval bullets rewritten to embed 'gold-standard promotion pipeline,' 'no agent reaches production without passing quality and safety thresholds,' and 'LLM-as-judge evaluation framework' | Mirror JD's exact language where experience genuinely matches |
| BRAIN project condensed to single bullet foregrounding MLflow experiment tracking | MLflow is a Databricks product and a preferred qualification; space optimization required condensing this project while preserving the NeurIPS credential |
| IBM and BofA roles condensed to single bullets each | Low relevance to agentic platform PM role; space required for higher-relevance content; minimum 1 bullet per role rule maintained |
| Deep Learning Education Platform project removed | Space constraint — 2-page target; lowest relevance to agentic platform PM role among projects; all other projects retained |
| Lawrence Berkeley National Laboratory entry removed from projects | Space constraint — 2-page target; NeurIPS credential preserved within BRAIN project bullet |
JD analysis (20 key phrases)
Key phrases: agentic platformmanaged agent runtimeMCP connectorsintelligence layerevaluation frameworkdeveloper experienceself-service by constructionidea to production in <4 weeksgoverned tool invocationmulti-step orchestrationdurable executionmodel gateway abstractionconnector SDKgold-standard promotion pipelineLLM-as-judgecontext window managementtime-to-productionenterprise-grade quality, security, and reliabilitycross-functional initiativesplatform strategy and roadmap
Hard requirements:
- 8+ years product management experience
- 3+ years internal platform, infrastructure, or developer-experience products
- Deep experience building platforms that other teams build on
- Demonstrated experience with AI/ML platforms, agent frameworks, LLM-powered applications, or agentic systems
- Strong technical foundation — architecture diagrams, trade-off discussions with engineers
- Experience defining and shipping developer experiences: SDKs, CLIs, templates, documentation, self-service workflows
- Proven ability to lead cross-functional initiatives across 4+ teams without direct authority
- Strong written communication — strategy docs, PRDs, executive briefs at VP/CIO level
Preferred qualifications:
- Experience with Databricks, Lakehouse architecture, Unity Catalog, MLflow, or Delta Lake
- Familiarity with LangGraph, LangChain, or similar agent orchestration frameworks
- Familiarity with MCP (Model Context Protocol), A2A, or AG-UI protocols
- Experience building AI evaluation frameworks — LLM-as-judge, red-teaming, automated quality scoring
- Experience with design systems, component libraries, or frontend platform work
- Background in enterprise SaaS platform consolidation or migration
Per-role mapping (10 roles scored)
| role | score | reframe angle | JD phrases that map |
|---|---|---|---|
| Streamio AI — Founder & CEO | 5/5 | Agentic platform builder — agent runtime, MCP connectors, multi-agent orchestration, developer tooling | managed agent runtime, MCP connectors, governed tool invocation, multi-step orchestration, connector SDK, developer experience, self-service by construction, model gateway abstraction |
| Fintellect AI — Founder & CEO | 4/5 | Intelligence layer and multi-provider model gateway — RAG, domain agents, LLM orchestration | intelligence layer, model gateway abstraction, context window management, RAG, domain-specific, governed tool invocation |
| Intuit — Staff Product Manager | 5/5 | Enterprise developer platform at scale — SDK/DevPortal, self-service, governance, 675M+ engagements | developer experience, self-service by construction, SDK, time-to-production, enterprise-grade quality, security, and reliability, platform strategy and roadmap, gold-standard promotion pipeline, governed tool invocation |
| Splunk — Senior Product Manager | 3/5 | Platform infrastructure PM — microservices, query performance, cross-functional roadmap | platform strategy and roadmap, cross-functional initiatives, enterprise-grade quality |
| Kaiser Permanente — SOA Technical PM | 2/5 | Enterprise platform infrastructure — managed services, scalability, governance | enterprise-grade quality, security, and reliability |
| IBM — Software Engineer | 1/5 | Technical foundation — enterprise software engineering | — |
| Bank of America Merrill Lynch — Tech MBA Associate | 1/5 | Quantitative analytical foundation | — |
| RL Workbench — Project | 4/5 | AI evaluation framework and post-training platform — LLM-as-judge analog, benchmarking, quality gates | evaluation framework, LLM-as-judge, evaluation gates, CI/CD |
| aeval — Project | 5/5 | AI evaluation platform with safety gates and CI/CD — direct analog to JD's evaluation and quality framework | evaluation framework, LLM-as-judge, gold-standard promotion pipeline, mandatory evaluation gates, safety thresholds, CI/CD |
| BRAIN — Project | 3/5 | ML platform credibility — MLflow, NeurIPS, production ML engineering | MLflow, AI/ML platforms |
Tailored summary
Technical Product Leader with 12+ years building agentic AI platforms, developer-facing SDKs, and enterprise infrastructure at scale — from shipping self-service developer platforms serving 675M+ engagements at Intuit to building multi-agent orchestration frameworks with MCP connectors and RAG intelligence layers as a founder. Deep hands-on experience with agent runtimes, LLM evaluation pipelines, model gateway abstraction, and governed tool invocation. Proven ability to drive cross-functional platform strategy from 0-to-1 through enterprise scale, communicate roadmaps at CTO/VP level, and reduce time-to-production from weeks to minutes. NeurIPS published researcher; MLflow practitioner.