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Own and build foundational backend services, APIs, and data infrastructure (auth, data models, pipelines) powering the compensation platform. Design generalized platform solutions, lead large ambiguous cross-team projects, and deliver scalable, maintainable systems.

Partner with Marketing to analyze Pave's compensation dataset and produce published data stories, reports, and customer-facing data products; field data questions from stakeholders; build lightweight measurement frameworks; and translate complex findings into clear narratives that drive product and business impact.

Own full-cycle technical recruiting for R&D (Engineering, Product, Design, Data): source passive candidates, partner with hiring managers, manage interviews and offers, leverage Pave compensation data to close candidates, run pipeline reporting in Greenhouse/Gem, and use AI tools to scale sourcing and outreach.

Build Pave's AI compensation analyst: design and implement agentic LLM systems that reason over proprietary compensation data and execute workflows. Collaborate with engineers and data scientists to ship end-to-end production features, architect retrieval and agentic pipelines, and drive product decisions with strong product instincts and ownership.

Build and own foundational services, APIs, and data infrastructure for Pave's compensation platform. Implement authentication/authorization, data pipelines, and models; drive large cross-team initiatives with a focus on scalability, maintainability, and product-led platform solutions.