Principal Engineer, Product Engineering

Details

• You have designed and operated large-scale distributed systems where reliability, scalability, maintainability, and operational excellence matter.
• You have deep experience driving architecture and technical direction across multiple teams, organizations, or product domains.
• You have strong systems-thinking instincts and can reason effectively about platform boundaries, distributed systems constraints, developer ergonomics, and long-term technical sustainability.
• You have experience building customer-facing product systems across clients, APIs, distributed services, cloud infrastructure, and data platforms.
• You have experience building or scaling event-driven systems, microservices architectures, or shared platform infrastructure in production environments.
• You have practical experience integrating AI or ML capabilities into production applications and understand the engineering tradeoffs involved in introducing AI into trust-sensitive product experiences.
• You have strong instincts for privacy-preserving and security-conscious system design, including thoughtful handling of telemetry, user data, permissions, and auditability.
• You are effective at driving alignment across teams with different incentives, priorities, and technical perspectives.
• You communicate clearly with engineers, executives, and cross-functional partners, and can explain complex technical tradeoffs in practical terms.
• You are comfortable operating in ambiguity and helping organizations make durable technical decisions before every variable is known.
• Experience in identity, authentication, authorization, secrets management, enterprise security, or trust-oriented product domains.
• Experience building large-scale event-driven or multi-region distributed systems in cloud environments.
• Experience building cross-platform applications or shared platform architectures at scale.
• Experience with developer platforms, internal engineering frameworks, CI/CD systems, or large-scale infrastructure modernization initiatives.
• Experience integrating LLMs or AI-assisted workflows into customer-facing SaaS applications.
• Experience with endpoint trust, browser or extension security, enterprise administration workflows, or device posture systems.
• Experience mentoring engineers and raising the engineering bar across organizations through technical leadership and operational excellence.
• Define architecture and technical direction for core product capabilities spanning clients, distributed services, data platforms, and shared infrastructure.
• Establish engineering standards and reusable architectural patterns for scalable, maintainable, and resilient product systems across Product Engineering.
• Drive long-term technical strategy across critical product areas, balancing immediate delivery needs with scalability, operational excellence, and platform sustainability.
• Partner closely with Product, Design, Security, Privacy, Infrastructure, and Data teams to ensure technical decisions support both customer outcomes and long-term operational durability.
• Guide how AI-powered capabilities are integrated into customer-facing product experiences, ensuring systems are reliable, observable, operationally safe, and aligned with customer trust expectations.
• Define engineering expectations for AI-enabled product systems, including evaluation frameworks, rollout safety, telemetry, fallback behavior, auditability, and operational controls.
• Establish shared platform capabilities and infrastructure patterns that allow teams to build product features consistently across clients, services, APIs, and AI-assisted workflows.
• Influence and drive key architectural decisions around distributed systems design, event-driven architectures, synchronization models, scalability, performance, reliability, extensibility, and platform interoperability.
• Help teams navigate difficult technical tradeoffs, unblock large cross-functional initiatives, and reduce systemic engineering complexity across the organization.
• Raise the operational bar for production systems through stronger reliability practices, observability standards, incident readiness, performance analysis, and engineering discipline.
• Mentor and influence engineers across the organization through technical leadership, architecture reviews, design guidance, and hands-on problem solving.
• Durable architectural patterns that enable teams to move faster with less duplication and lower operational overhead.
• Product systems that scale reliably across platforms, enterprise environments, and growing customer complexity.
• Engineering teams making more consistent technical decisions with clearer standards and stronger shared foundations.
• AI-powered product experiences that are useful, measurable, trustworthy, and operationally safe.
• Reduced systemic friction across development, delivery, observability, and cross-team coordination.
• Stronger operational resilience, including improved reliability, debuggability, rollout safety, and incident response readiness.
• Technical investments that improve long-term engineering velocity instead of creating organizational drag or platform fragmentation.