← anthropic / Product Manager, Developer Productivity
tailored_resume_v2 / art_CEggiKJnkO0
role
model
anthropic/claude-sonnet-4.6
created
2026-05-19T20:59
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What changed for anthropic
| change | why it matters |
|---|---|
| Summary rewritten to lead with developer platform infrastructure credentials and 675M+ engagement metric | JD's first hard requirement is 7+ years PM experience with developer tooling, build systems, CI/CD, or platform infrastructure — Intuit is the strongest proof point |
| Summary explicitly names 'human-agent collaboration' and 'what developer productivity means when Claude writes, tests, and reviews code' | JD's most distinctive requirement is a strong thesis on AI reshaping software development — mirroring JD's exact framing signals cultural and strategic alignment |
| Intuit role leads experience section and retains 7 bullets; first bullet leads with 675M+ scale and TPS throughput | Highest relevance score (5/5); JD values enterprise-scale build/CI infrastructure and internal platform adoption — metrics belong in first 2 bullets per anti-patterns |
| Intuit drift detection bullet reframed as 'automated dependency management capability' | JD explicitly lists 'automated dependency management' as a product strategy responsibility — accurate reframe of the same OpenRewrite/JAR work |
| Streamio role title reframed to 'AI-Native Developer Tooling Platform' | JD seeks someone who has 'shipped AI-native developer tooling' — the MCP SDK, OpenClaw orchestration, and embedded terminal are the strongest proof points for this preferred qual |
| Streamio bullets reordered to lead with MCP SDK + OpenClaw agent orchestration | JD's most forward-looking requirement is defining 'developer tooling primitives for human-agent collaboration' — these bullets are the most direct evidence |
| RL Workbench project moved to lead the projects section and reframed to emphasize GPU/CUDA accelerator toolchain benchmarking | JD lists 'accelerator toolchain management (GPU, TPU, Trainium)' as a preferred qual and core roadmap responsibility — this is the only direct evidence of hands-on GPU toolchain work |
| aeval project reframed to emphasize CI/CD integration, automated safety gates, and agent-driven test generation governance | JD explicitly calls out 'agent-driven test generation' and 'governance frameworks that let teams safely delegate work to autonomous systems' as product strategy responsibilities |
| Fintellect condensed to 1 bullet focusing on multi-provider LLM orchestration architecture | Lower relevance to DevProd role; retaining 1 bullet preserves the multi-agent platform credibility without consuming space needed for higher-relevance content |
| Kaiser Permanente reframed to emphasize 'internal platform adoption at scale' with 200+ internal customers | JD preferred qual explicitly states 'you know that the best internal tool is the one engineers actually use, and you've driven adoption through product quality rather than mandate' |
| Deep Learning Education Platform project removed | Lowest relevance to this role; space optimization for 2-page target — teaching experience section already covers educational credentials |
| Lawrence Berkeley National Laboratory entry removed from projects | Space optimization; NeurIPS paper already establishes research credibility more concisely |
JD analysis (20 key phrases)
Key phrases: developer productivitybuild and CI infrastructuredeveloper experienceAI-native acceleration layeraccelerator toolchain managementhuman-agent collaborationautonomous collaboratorsgovernance frameworksvelocity, reliability, securityengineering velocitydeveloper tooling primitivesagent-driven test generationautomated dependency managementproductivity metricsmonorepoCI/CD pipelinesdeveloper environmentsinternal platform adoption0-to-1frontier AI
Hard requirements:
- 7+ years PM experience with developer tooling, build systems, CI/CD, or platform infrastructure
- Experience taking technical platform products from 0-to-1 and scaling to demanding engineering customers
- Track record balancing velocity, reliability, security trade-offs across multiple engineering personas
- Ability to internalize complex technical systems (build systems, monorepos, CI pipelines, accelerator toolchains)
- Strong thesis on how AI reshapes software development and agent-driven workflows
Preferred qualifications:
- Built or scaled developer productivity / build systems / CI/CD for large engineering orgs (Bazel, Buck, monorepos)
- Experience defining engineering productivity metrics (DORA, SPACE, or custom frameworks) in AI-agent contexts
- Familiarity with accelerator toolchain ecosystems (CUDA/GPU, TPU, AWS Neuron/Trainium)
- Shipped AI-native developer tooling — code assistants, agent-based automation, AI-integrated IDEs
- Scaled through hypergrowth in AI/ML or developer tools companies
- Internal platform adoption driven through product quality rather than mandate
Per-role mapping (10 roles scored)
| role | score | reframe angle | JD phrases that map |
|---|---|---|---|
| Intuit — Staff PM Developer Frameworks & Platform Infrastructure | 5/5 | Developer platform infrastructure at enterprise scale — SDK tooling, CI/CD, build systems, developer onboarding, and internal platform adoption | developer experience, build and CI infrastructure, developer tooling primitives, internal platform adoption, velocity, reliability, security, engineering velocity, 0-to-1, CI/CD pipelines, automated dependency management, productivity metrics |
| Streamio AI — Founder & CEO | 4/5 | AI-native developer tooling — agent orchestration, MCP integration, autonomous workflow primitives | AI-native acceleration layer, autonomous collaborators, governance frameworks, human-agent collaboration, developer tooling primitives, 0-to-1 |
| Fintellect AI — Founder & CEO | 2/5 | Multi-agent LLM orchestration and AI platform architecture | human-agent collaboration |
| Splunk — Senior PM Search Orchestration | 4/5 | Platform infrastructure PM — microservices, performance optimization, developer-facing APIs | velocity, reliability, security, build and CI infrastructure, productivity metrics, developer experience |
| Kaiser Permanente — SOA Technical PM | 3/5 | Internal platform at scale — observability infrastructure, capacity planning | internal platform adoption, velocity, reliability, security |
| IBM — Software Engineer Business Intelligence | 2/5 | Engineering depth and enterprise software credibility | — |
| Bank of America Merrill Lynch — Tech MBA Associate | 1/5 | Quantitative analytical foundation | — |
| RL Workbench Project | 5/5 | Accelerator toolchain management and AI-native developer tooling — directly maps to GPU/TPU toolchain and frontier AI build infrastructure | accelerator toolchain management, frontier AI, developer environments, productivity metrics |
| aeval Platform | 4/5 | AI-native evaluation infrastructure with CI/CD integration and automated safety gates — maps to agent-driven test generation and governance | agent-driven test generation, governance frameworks, CI/CD pipelines, productivity metrics, automated dependency management |
| AutoEval Project | 3/5 | Automated evaluation tooling reducing toil — maps to agent-driven test generation | agent-driven test generation, toil eliminated |
Tailored summary
Technical Product Manager with 12+ years building developer-facing platforms and AI-native tooling at scale — including developer frameworks, SDK tooling, and CI/CD infrastructure serving 675M+ engagements at Intuit, and a hands-on RL post-training workbench benchmarking GRPO/DPO across GPU/CUDA accelerator toolchains today. Deep expertise taking 0-to-1 platform products to enterprise scale, defining the developer experience model across build systems and internal tooling, and driving internal platform adoption through product quality. NeurIPS published researcher with a strong thesis on human-agent collaboration and what developer productivity means when Claude writes, tests, and reviews meaningful portions of a codebase.