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Strong brand and remote role, but senior specialized data-platform focus limits applicant density.
High — requires specialized data-platform and distributed-systems experience, less transferable outside data-heavy SaaS environments.
High — requires senior platform leadership, distributed-systems depth, and multi-tenant data platform experience.
Lead engineering to design and evolve an AI-ready context data platform supporting structured, unstructured, vector, and graph data systems.
Own delivery of core platform capabilities including high-scale ingestion, validation frameworks, multi-tenant isolation, and sub-second search APIs with 99.99% availability targets.
Architect and operationally scale distributed systems, define engineering metrics, and build/mentor high-performing platform engineering teams.
Experience building or owning foundational data/platform systems such as data ingestion frameworks, metadata platforms, multi-tenant SaaS infrastructure, or distributed serving layers.
Proven engineering leadership experience managing and scaling platform or data-focused teams, including managing managers.
Deep knowledge of distributed systems, cloud-native architectures, and operating high-availability platforms with strong SLO adherence.
Work Experience Required: Not explicitly mentioned in the JD.
Technical leader with hands-on experience owning large-scale, complex data platform and infrastructure systems actively shaping technical direction.
Experience operating in data platform or infrastructure environments powering enterprise SaaS with emphasis on reliability and scalability under strict SLOs.
Strategic thinker combining systems design with people management to connect technical decisions to product strategy and team growth in evolving environments.