Warp began with the vision of reimagining one of the fundamental dev tools—the terminal—to make it more usable and powerful for all developers. As AI has advanced, Warp has evolved beyond its terminal roots into the platform for Agentic Development: a workbench for dispatching agents to code, deploy, and debug production software. With over 700k active developers and revenue that grew over 44x last year, Warp is now one of the fastest growing startups in the exploding AI development space. We believe that soon developers will be “tech leads” for groups of agents; rather than opening a code editor to write code or a terminal to write commands, they will open Warp and prompt their computer to build features, fix bugs, and diagnose production issues. With its starting point as a reimagined command line, Warp is well-positioned to support agent-first workflows: It sits at the lowest level in the dev stack, has access to all of a developer’s context, and is set up for multitasking and long-running processes. In addition, Warp has state-of-the-art code editing features and built-in team knowledge sharing. It’s the right interface for the agentic future. Our mission has remained the same even as AI has advanced: to empower developers to ship better software more quickly, freeing them to focus on the creative and rewarding aspects of their work. For more information on our team and culture, we highly recommend reading our How We Work. Warp is scaling its enterprise motion around Oz Cloud Agents — cloud-connected background agents that run from events, schedules, or integrations, giving teams scalable automation with shared observability. As enterprises adopt Oz, they need hands-on technical guidance to deploy production agents — configuring environments, designing agent workflows, setting up self-hosted infrastructure, and iterating on prompts and skills. We're hiring an Implementation Engineer to be the dedicated technical lead for these engagements. This person will run our structured Implementation Support program, working directly with customer engineering teams from use case selection through production deployment. You'll sit at the intersection of engineering and enterprise GTM; building alongside customers, not just advising. You'll architect agent workflows, configure Docker environments, write skills and prompts, debug integrations, and guide self-hosted deployments. You'll also work closely with Product and Engineering to translate field learnings into product improvements, shaping the platform based on what you see in the field.
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
11-50 employees