Privacy Engineer

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.

Privacy is central to building products people trust. As a Privacy Engineer on 1Password’s Privacy Engineering team within the Security organization, you’ll build technical controls, automation, and tooling that help protect personal data across our products and systems.

You’ll combine software engineering with artificial intelligence (AI)-assisted approaches to improve privacy reviews, data handling, retention, deletion, and telemetry practices at scale. Working closely with Engineering, Product, Data, and Legal and Privacy partners, you’ll help make privacy by design practical, consistent, and durable across a cloud-based product environment.

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:

Experience building and shipping production software in a Software as a Service (SaaS), cloud, or similarly complex engineering environment.

Proficiency in at least one backend programming language, such as Python, TypeScript, or Go, along with strong fundamentals in testing, debugging, version control, and maintainable software design.

Experience building with large language model (LLM) systems or comparable AI frameworks, including agents, tool-use pipelines, or multi-step orchestration workflows.

Experience integrating software with external systems through application programming interfaces (APIs), databases, ticketing systems, CI/CD pipelines, or data platforms.

Practical experience with privacy or data-handling concepts such as data minimization, access controls, retention and deletion, consent, or privacy-conscious telemetry, and the ability to translate established privacy requirements into concrete engineering work.

Ability to take ownership of well-defined projects or workstreams from implementation through delivery and collaborate effectively with Security, Engineering, Product, Data, and Legal and Privacy partners.

Preferred: Experience with privacy regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), or the California Privacy Rights Act (CPRA), as well as data subject rights workflows, data inventories, third-party integrations, threat modeling, privacy reviews, prompt design, LLM output validation, reliability patterns, or privacy safeguards for AI-assisted features.

What you can expect:

Build and deploy agent-based workflows for privacy engineering processes such as privacy review intake, data subject rights requests, data inventory updates, and telemetry classification.

Build AI-assisted tooling that helps engineering teams identify privacy risks earlier and apply appropriate safeguards with less manual effort.

Implement and improve privacy controls related to authorization, data scoping, retention and deletion, consent signals, and responsible data access.

Integrate privacy tooling with engineering workflows and systems, including continuous integration and continuous delivery (CI/CD), code review, data catalogs, ticketing platforms, and internal services.

Improve the handling of logs and telemetry through classification, minimization, and redaction practices that support useful visibility without unnecessary data collection.

Improve manual and semi-automated privacy processes by developing scalable solutions that increase speed, consistency, and auditability.