Implementation Engineer, Warp

• You have 3+ years of experience in implementation engineering, solutions engineering, forward-deployed engineering, or a similar customer-facing technical role
• You have a strong software engineering background — you're comfortable writing production-quality code, debugging distributed systems, and working across the stack
• You have experience with Docker, CI/CD pipelines, cloud infrastructure (understanding of container orchestration, image management, and deployment patterns), Kubernetes, Linux, and cloud providers (AWS, GCP, Azure)
• You're familiar with AI/LLM concepts — prompt engineering, agent architectures, tool use, and evaluation of non-deterministic systems
• You have experience working with developer tools, DevOps platforms, or infrastructure software
• You can manage multiple concurrent customer engagements while maintaining high quality and clear communication
• You have excellent communication skills — you can explain complex technical concepts clearly to both engineering leads and executive stakeholders
• So if you’re excited about this role, but your past experience doesn’t align perfectly with every qualification in this job description – we encourage you to apply anyways

Desirable

• 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
• Lead implementation engagements end-to-end. Run our multi-week implementation support program — from kickoff (requirements gathering, use case selection, success criteria definition) through weekly implementation sessions to wrap-up (outcome review, ROI validation, expansion planning)
• Architect agent workflows with customers. Help enterprise teams design agent architectures for their specific use cases — selecting agent triggers, configuring sandboxed environments, and structuring multi-step agent workflows
• Build alongside customers. Write and iterate on agent prompts, skills, and configurations. Set up environments, secrets, MCP servers, and integrations. Debug agent runs using session sharing and observability tools
• Guide self-hosted deployments. For enterprises running agents on their own infrastructure, help configure self-hosted workers, Docker daemon connectivity, private registries, and task routing
• Develop reusable implementation patterns. Document architecture patterns, reference implementations, and best practices that accelerate future deployments. Contribute to the Oz skill and template ecosystem
• Be the voice of the customer to Product and Engineering. Surface implementation friction, feature gaps, and common pain points. Translate customer needs into actionable product feedback that shapes the Oz platform roadmap
• Provide ongoing technical support. Respond to customer questions via Slack with same-business-day SLA. Troubleshoot agent failures, environment issues, and integration problems