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This role sits at the intersection of platform infrastructure and agent systems engineering. You'll build and maintain the core infrastructure, CI/CD pipelines, and platform services that underpin our machine learning initiatives and go further in designing the harnesses, sandboxes, and evaluation frameworks that let AI agents be developed, tested, and trusted in production. You'll work on systems that directly impact marketing, sales, service, and product growth verticals across the organization. This isn't a traditional infrastructure role. You should be comfortable wearing multiple hats of software engineering, agent systems design, and evaluation tooling. We're looking for engineers who think in flywheels: build →evaluate → improve → ship → repeat. 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You'll join a growing team and help shape our forward-looking payments products designed for small business. The Senior Product manager leads initiatives to improve the developer experience across the platform, including API design and usability, SDKs and embedded payment modules, webhook and events, developer documentation and integration guides, testing tools and sandbox environments. 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Bellevue The Experience We are seeking a Principal Software Engineer to join our Platform Trust Intelligence and Security (PTIS) team - the runtime substrate that detects, isolates, and contains threats across an enterprise pivoting to autonomous AI. As organizations deploy AI agents that execute multi-step reasoning, access sensitive data, and take real-world actions, a new class of security risk emerges. Agents operating outside their intended scope can exfiltrate data, probe permission boundaries, or trigger privileged operations at a speed and scale no human user can match - while appearing to function exactly as designed. Product-layer guardrails define the operating envelope; this platform catches what slips through. You will design and build the secure runtime, telemetry, detection, and containment layers that let us observe every agent's behavior, run untrusted agent code under hard isolation, score it against learned baselines, and intervene safely when it deviates - without ever crossing a tenant boundary or stalling a legitimate workload. This is a hands-on principal role at the intersection of platform engineering, secure runtimes, and applied machine learning (ML). 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