Principal Engineer, Product Engineering

Remote (United States | Canada)Full-TimePrincipal

SalaryUSA-based roles: $246,000 - $369,000 USD; Canada-based roles: $228,000 - $342,000 CAD. Plus equity grant and incentive programs.

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Job Details

Required Skills: CI/CDMicroservicesDistributed Systems

Requirements

Deep experience designing and operating large-scale distributed systems with a focus on reliability, scalability, and maintainability.
Proven track record of driving architecture and technical direction across multiple teams, organizations, or product domains.
Strong systems-thinking instincts with the ability to reason about platform boundaries, distributed system constraints, and developer ergonomics.
Experience building customer-facing product systems across clients, APIs, distributed services, cloud infrastructure, and data platforms.
Hands-on experience scaling event-driven systems, microservices, or shared platform infrastructure in production environments.
Practical experience integrating AI or ML capabilities into production applications, including understanding engineering tradeoffs in trust-sensitive contexts.
Strong understanding of privacy-preserving and security-conscious system design, including telemetry, user data, permissions, and auditability.
Effective at driving cross-team alignment and communicating complex technical tradeoffs to both technical and executive audiences.
Ability to operate in ambiguity and lead durable technical decision-making.

Responsibilities

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.
Influence and drive key architectural decisions around distributed systems design, event-driven architectures, synchronization models, scalability, performance, reliability, extensibility, and platform interoperability.
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.

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