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Demandbase, Inc. is seeking a Staff DevOps Engineer to join the DevEx team. You will define multi-quarter platform strategy across build, test, deploy, and operate stages for services and data pipelines on AWS and GCP, acting as a force multiplier for reliability and scale.
You will drive self-service platform adoption, improve observability and security, and mentor senior engineers to elevate the organization’s engineering practices and delivery velocity.
Introduction to Demandbase:
Demandbase is the only pipeline AI platform that empowers GTM teams to automate growth at scale. With a unified view of data, insights, actions, and outcomes, B2B enterprises can seamlessly align and execute their account-based GTM strategies with confidence. Thousands of businesses trust Demandbase to maximize revenue, minimize waste, and consolidate their data and tech stacks - all in one platform.
As a company, we're as committed to growing careers as we are to building world-class technology. We invest heavily in people, our culture, and the community around us. We have also continuously been recognized as One of The Best Places To Work in the San Francisco Bay Area by Fortune, and One of The 60 Best Companies To Sell For by Selling Power. Our offices are located in San Francisco, New York, Austin, Seattle, India, and the United Kingdom.
As a Staff DevOps Engineer on the Developer Experience (DevEx) team, you will set the technical direction for the platforms, tooling, and workflows that every engineering team at Demandbase depends on to ship reliably to production. This is not a single-team execution role you will define multi-quarter platform strategy across build, test, deploy, and operate stages for services and data pipelines running on AWS and GCP, and you'll be the person other senior and staff engineers across the org come to when a platform decision has broad blast radius.
You'll act as a force multiplier at organizational scale: abstracting infrastructure complexity into paved roads, driving adoption of self-service platforms, and embedding reliability, security, costawareness, and observability. You are fluent with AI-assisted and agentic engineering workflows and are expected to help define how the broader engineering org adopts these tools safely and effectively. This role is critical to improving local-to-production parity, reducing cognitive load fleetwide, and sustaining high release velocity across our Kubernetes-based services and data platforms.
You'll combine technical strategy, platform product thinking, and hands-on systems leadership to make reliable delivery the default for engineering teams.