← elastic / Principal Product Manager, AI agents - Search
tailored_resume_v2 / art_0FQxQbaAgME
role
model
anthropic/claude-sonnet-4.6
created
2026-05-22T21:39
↓ Download .docx ↓ Download .pdf PDF requires LibreOffice installed
What changed for elastic
| change | why it matters |
|---|---|
| Summary rewritten to lead with AI agent orchestration and RAG/context engineering credentials | JD's primary requirement is deep understanding of AI agents, RAG architectures, and context engineering for the Agent Builder product |
| Fintellect AI moved to lead the Experience section, ahead of Streamio AI | Fintellect's RAG pipeline + ChromaDB vector store + multi-provider LLM orchestration is the most direct match to Elastic's retrieval/relevance and context engineering focus |
| Fintellect bullets reframed around 'context-engineered AI agents' and 'agentic workflow design' | Mirrors JD's key phrases: context engineering, agentic workflows, Agent Builder |
| Streamio OpenClaw bullet reframed to emphasize 'coordinated agentic workflows' and 'context routing' | JD explicitly calls out agent orchestration and context layer as core Agent Builder capabilities |
| Splunk role reframed as 'retrieval and relevance' domain expertise | Elastic is a search company; Splunk search orchestration experience is a direct domain signal and differentiator |
| Splunk query performance bullet reframed to emphasize 'benchmarking and evaluation rigor' | JD explicitly calls out 'benchmarking and evaluations of agent capabilities' as a key responsibility |
| aeval project moved to lead the Projects section | JD calls out 'strategy for benchmarking and evaluations of agent capabilities' as a core responsibility; aeval is the strongest proof point |
| Intuit bullets reordered to lead with 675M+ scale metric | JD requires demonstrated scale on data-intensive products; enterprise scale should not be buried |
| Intuit framing shifted to emphasize 'developer persona advocacy' language | JD explicitly calls out 'advocate for the developer persona' as a success criterion |
| Deep Learning Education Platform project removed to save space | Lowest relevance project; page target requires condensing least-relevant content |
| Lawrence Berkeley Lab entry folded into BRAIN project context | Space optimization; NeurIPS paper is the stronger credential signal |
JD analysis (20 key phrases)
Key phrases: AI agentsAgent Buildercontext engineeringRAG architecturesvector databasesagentic workflowsbenchmarking and evaluationsretrieval and relevancecontext layerenterprise customersdeveloper personacloud infrastructurehyperscalersLLMsdata-intensive productsroadmapbias to actionmatrixed organizationopen source projectsevangelize
Hard requirements:
- 10+ years product management or solution delivery for technical/cloud/platform products
- Deep understanding of LLMs, RAG architectures, vector databases, context engineering
- Experience leading data-intensive products from inception through launch and iterative growth
- Ability to work with engineers and data scientists on complex technical challenges
- Stakeholder alignment and roadmap ownership across matrixed organizations
- Outstanding written and verbal communication for technical and executive audiences
Preferred qualifications:
- Experience with AI agent frameworks and orchestration
- Familiarity with hyperscaler ecosystems (Google, Amazon, Microsoft)
- Developer persona advocacy and community evangelism
- Benchmarking and evaluation strategy for AI/ML capabilities
- Open source project experience
Per-role mapping (7 roles scored)
| role | score | reframe angle | JD phrases that map |
|---|---|---|---|
| Streamio AI — Founder & CEO | 4/5 | AI agent orchestration builder and context engineering — maps directly to Agent Builder product | AI agents, agentic workflows, context layer, Agent Builder, open source projects, bias to action |
| Fintellect AI — Founder & CEO | 4/5 | RAG architecture and vector database product ownership — direct match to context engineering and retrieval/relevance | RAG architectures, vector databases, LLMs, context engineering, AI agents, agentic workflows |
| Intuit — Staff Product Manager | 5/5 | Enterprise-scale platform PM with developer persona advocacy and data-intensive product leadership | cloud infrastructure, developer persona, data-intensive products, roadmap, matrixed organization, enterprise customers, hyperscalers |
| Splunk — Senior Product Manager | 4/5 | Search platform PM with retrieval/relevance and data pipeline experience — strong Elastic domain fit | retrieval and relevance, cloud infrastructure, data-intensive products, roadmap, enterprise customers |
| Kaiser Permanente — SOA Technical PM | 2/5 | Enterprise platform scale and infrastructure credibility | cloud infrastructure, enterprise customers |
| IBM — Software Engineer | 1/5 | Enterprise software engineering foundation | enterprise customers |
| Bank of America Merrill Lynch — Tech MBA Associate | 1/5 | Quantitative analysis foundation | — |
Tailored summary
Principal Product Manager with 12+ years leading enterprise-scale, data-intensive platform products — and a hands-on builder of AI agent orchestration frameworks, RAG retrieval pipelines, and LLM evaluation infrastructure. Architected OpenClaw multi-agent orchestration with subagent delegation and context routing, and built RAG pipelines with ChromaDB vector stores and multi-provider LLM fallback — the exact context engineering stack at the core of agentic workflows. Scaled developer-facing platforms to 675M+ engagements at Intuit; owned search orchestration and retrieval at Splunk. NeurIPS published researcher; UC Berkeley engineering.