# Principal Engineer, Product Engineering

**Company:** [1Password](https://hotfix.jobs/companies/1password)
**Location:** Remote
**Role:** Fullstack Engineering
**Experience:** 7+ years
**Skills:** Distributed Systems, Microservices, Event-Driven Systems, Ai/Ml Integration, Cloud Infrastructure, Data Platforms, Security Design, Privacy-Preserving Systems, System Architecture, LLMs, CI/CD, Cross-Platform Development
**Posted:** 2026-06-29

> Principal Engineer defining technical direction and architecture for 1Password's core product experiences across clients, distributed services, data platforms, and infrastructure. Requires deep expertise in large-scale distributed systems, AI integration, security/privacy by design, and driving organization-wide technical standards.

## Job Description

## 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.
- 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.

## Requirements
- Designed and operated large-scale distributed systems where reliability, scalability, maintainability, and operational excellence matter.
- Deep experience driving architecture and technical direction across multiple teams, organizations, or product domains.
- Strong systems-thinking instincts and can reason effectively about platform boundaries, distributed systems constraints, developer ergonomics, and long-term technical sustainability.
- Experience building customer-facing product systems across clients, APIs, distributed services, cloud infrastructure, and data platforms.
- Experience building or scaling event-driven systems, microservices architectures, or shared platform infrastructure in production environments.
- Practical experience integrating AI or ML capabilities into production applications and understand the engineering tradeoffs involved in introducing AI into trust-sensitive product experiences.
- Strong instincts for privacy-preserving and security-conscious system design, including thoughtful handling of telemetry, user data, permissions, and auditability.
- Effective at driving alignment across teams with different incentives, priorities, and technical perspectives.
- Communicate clearly with engineers, executives, and cross-functional partners, and can explain complex technical tradeoffs in practical terms.
- Comfortable operating in ambiguity and helping organizations make durable technical decisions before every variable is known.

## Nice-to-Haves
- 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.

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