Principal Engineer, Product Engineering

1Password is growing. We’ve surpassed $400M in ARR and we’re continuing to accelerate, earning a spot on the Forbes Cloud 100 for four years in a row and teaming up with iconic partners like Oracle Red Bull Racing. About 1Password At 1Password, we’re building the foundation for a safe, productive digital future. Our mission is to unleash employee productivity without compromising security by ensuring every identity is authentic, every application sign-in is secure, and every device is trusted. We innovated the market-leading enterprise password manager and pioneered Unified Access Management, a new cybersecurity category built for the way people and AI agents work today. As one of the most loved brands in cybersecurity, we take a human-centric approach in everything from product strategy to user experience. Over 180,000 businesses, from Fortune 100 leaders to the world’s most innovative AI companies, trust 1Password to help their teams securely adopt the SaaS and AI tools they need to do their best work. If you're excited about the opportunity to contribute to the digital safety of millions, to work alongside a team of curious, driven individuals, and to solve hard problems in a fast-paced, dynamic environment, then we want to hear from you. Come join us and help shape a safer, simpler digital future. We are hiring a Principal Engineer to help define the technical direction for core product experiences at 1Password. This is a senior individual contributor role for an engineer who can translate ambitious product strategy into systems that scale technically and operationally. You will drive architecture, engineering standards, and technical direction across the product ecosystem, working across client applications, distributed services, data platforms, and shared infrastructure to build experiences that are secure, reliable, performant, and maintainable.This is not a role scoped to a single team or subsystem. The expectation is organization-level technical leadership: shaping how Product Engineering approaches complex cross-cutting problems, guiding long-term architectural investments, and establishing the technical patterns and operational standards other teams build against. You will operate across the full lifecycle of product engineering work, from architecture and system design through production operations and long-term evolution. Success in this role requires balancing product velocity with engineering durability, making pragmatic technical tradeoffs, and driving alignment across teams with different priorities and constraints. You will help evolve the next generation of 1Password’s product architecture, including the responsible integration of AI capabilities into core product experiences. Security and privacy by default, cross-platform consistency, operational resilience, and enterprise-scale reliability are foundational requirements that must be reflected in every architectural decision. If you want to build systems used daily by millions of individuals and hundreds of thousands of businesses, and solve engineering problems where distributed systems, reliability, usability, security, and intelligent automation all matter simultaneously, this is that role. How we’re using AI today Our Engineering, Product, and Design teams are thoughtfully integrating AI across the full software and product development lifecycle to move faster without sacrificing quality or security. In practice, that looks like engineers using AI-assisted coding tools to accelerate reviews and catch bugs earlier, product managers synthesizing user research at scale, and designers rapidly prototyping and iterating with AI-generated mockups. We approach AI the same way we approach security: with clear principles, human accountability at every consequential decision point, and rigorous evaluation before anything ships to customers. This is a remote opportunity within Canada and the US.

What We're Looking For

• 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 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.

• 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.

• 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.

• Highlight concrete examples where you defined architecture for a distributed system; include diagrams or repo links if possible.
• Prepare to discuss how you balance rapid feature delivery with long‑term reliability—use specific trade‑off scenarios from past work.
• Demonstrate familiarity with security best practices; be ready to walk through a past security‑by‑design decision.
• Show experience with AI integration by describing a project where you added ML features without compromising safety.
• In the interview, ask about the current technical debt backlog to signal strategic thinking.
• Negotiate remote‑work stipend early; many remote roles include a home‑office allowance.
• Watch for vague answers around decision‑making authority—clarify the extent of technical autonomy before accepting.