1Password is growing. We’ve surpassed $500M 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.

At 1Password, we want our Go-To-Market teams to have the best tools, data, and AI available. We're looking for a Staff GTM Engineer to join Revenue Operations and own the architecture, development, and operation of the AI applications, agents, and data pipelines across our sales, marketing, and customer success stack.

This is a hands-on, cross-functional engineering role. You'll write and ship production code, set the technical direction for AI in GTM, and bring engineering rigor to the work: architecture reviews, testing, CI/CD (Continuous Integration/Continuous Delivery), and observability. You'll work closely with operations, systems, analytics, engineering, and security teams to turn ideas into reliable services that help revenue teams work faster and smarter.

Reporting into the Senior Director, GTM Engineering, this role is a remote opportunity within Canada and the USA.

How we’re using AI today

Across GTM, we’re transforming the way we work with AI. We expect every seller, CSM, and team member to become a power user, using it daily to work smarter and move faster. AI is already embedded in how we operate – from real-time coaching that sharpens how we sell and interact with customers, to surfacing insights that help us anticipate needs – creating more time for meaningful customer engagement. If you’re excited to reshape how you think, make decisions, and drive growth with AI, you’ll feel right at home here.

Note: All go-to market roles will have an in-person onboarding in Toronto.

What we're looking for

• Bring 6 or more years of engineering experience, including ownership of production tools from initial design through deployment and ongoing operation.

• Work directly with GTM workflows and systems such as Salesforce, Clay, HubSpot, Outreach, Gong, and Gainsight, including their application programming interfaces (APIs) and data models.

• Build production agentic applications using prompt and context engineering, retrieval-augmented generation (RAG), vector databases, tool calling, evaluation frameworks, and observability.

• Translate business goals and pain points into clear technical requirements, explain tradeoffs in plain language, and collaborate effectively with non-technical GTM leaders and cross-functional partners.

• Write clean, tested, maintainable code and apply strong engineering practices, including version control, code review, debugging, and consistent coding standards.

• Deploy and operate production services on Amazon Web Services (AWS) or Google Cloud Platform (GCP), using containers or serverless infrastructure, infrastructure as code, continuous integration and continuous delivery (CI/CD), monitoring, and alerting.

• Use Structured Query Language (SQL) and data modeling to build reliable data pipelines between systems.