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Docker is seeking a Customer Experience Engineer – Technical (CXE-T) for the EMEA region to scale deep product adoption through technical enablement, structured Proof of Concepts, and high-impact technical assets. This is a post-sales technical subject matter expert role focused on technical depth and applied architecture guidance rather than traditional lifecycle management.
Key responsibilities include designing and delivering advanced technical sessions (webinars, live builds, architecture deep dives) for platform, DevOps, security, and engineering audiences; creating structured enablement series aligned to customer maturity stages; and developing repeatable technical learning paths that drive adoption beyond initial onboarding.
You will design scalable PoC frameworks that customers can adopt independently or via cohort-based execution, define technical success criteria and evaluation benchmarks for common adoption scenarios (policy enforcement, image integrity, SBOM visibility, secure pipelines), and translate Docker capabilities into practical architectural patterns. On exception, you'll lead 1:1 customer workshops or guided PoCs for complex or high-value technical initiatives.
The role involves producing deep technical assets including recorded walkthroughs, architecture reference guides, advanced implementation blogs, and reusable demo environments. You'll serve as a subject matter expert for non-support technical questions, providing architectural guidance across secure build pipelines, software supply chain integrity, container security and governance, AI/ML workload governance, and AI agent architecture patterns. You'll partner with Sales Engineers and Post-Sales teams to ensure technical continuity without owning deal cycles.
Required qualifications: 5+ years in Solutions Engineering, Technical Account Management, DevOps, Platform Engineering, or similar technical roles. Strong hands-on expertise in Docker and container ecosystems, secure software supply chain practices, CI/CD pipelines, and modern cloud-native architecture. Experience designing and executing structured PoCs with defined success criteria, presenting complex technical topics to senior engineering audiences, and producing technical blogs or deep technical content.
Preferred: hands-on experience with AI/ML development workflows, AI coding agent runtimes and sandboxed execution environments, Docker SBX and MCP Gateway, secure software supply chain practices (SBOM, artifact signing, provenance, SLSA), container image lifecycle management, Secure Software Development Lifecycle (SSDLC) practices, governance frameworks (NIST, EU AI Act), and experience designing reusable lab environments or reference architectures.
