Staff GTM Engineer

About the Role

At 1Password, 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. 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.

What You Can Expect

• Ship AI into the revenue workflow: Design, build, and run production agents and services for lead scoring, enrichment, routing, summarization, and personalized outreach across GTM systems.
• Own the GTM technical roadmap: Partner with RevOps and GTM leaders to find and prioritize the use cases worth building, and make the build vs. buy and architecture calls behind them.
• Build the platform others build on: Create shared APIs, integrations, and data pipelines that connect revenue systems, so each new use case ships faster than the last.
• Make AI measurable and safe to change: Put evaluations, monitoring, and staged rollouts around every AI workflow, and partner with Security and IT to protect customer data.
• Set the engineering bar for GTM: Establish standards for code review, linting, testing, CI/CD, and documentation. Mentor engineers and technical operators.
• Run what you build: Join the on-call rotation for your systems and lead incident response and follow-up fixes.