Customer Experience Engineer, CXE-T

Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.

We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.

The Customer Experience Engineer – Technical (CXE-T) is a post-sales technical subject matter expert responsible for scaling deep product adoption through 1:many technical enablement, structured Proof of Concepts (PoCs), and high-impact technical assets.

Unlike traditional program or lifecycle roles, this position is focused on technical depth and applied architecture guidance. The CXE-T designs and delivers scalable technical sessions, builds reusable PoC frameworks, produces advanced technical recordings and blogs, and serves as an escalation point for non-support Solutions Engineering–type questions across customer cohorts.

This role amplifies impact across large customer populations through structured enablement systems, while occasionally leading targeted 1:1 workshops for high-impact customers or strategic technical initiatives.

• Design and deliver advanced technical sessions (webinars, live builds, architecture deep dives, workshops) for platform, DevOps, security, and engineering audiences.

• Create structured enablement series aligned to customer maturity stages (e.g., secure SDLC, supply chain hardening, container governance).

• Develop repeatable technical learning paths that drive adoption beyond initial onboarding.

• 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 (e.g., policy enforcement, image integrity, SBOM visibility, secure pipelines).

• Translate Docker capabilities into practical architectural patterns customers can implement.

• On exception, lead 1:1 customer workshops or guided PoCs for complex or high-value technical initiatives.

• Produce deep technical assets:

  • Recorded walkthroughs

  • Architecture reference guides

  • Advanced implementation blogs

  • Reusable demo environments

• Build assets that directly support customer journey stages and remove common technical blockers.

• Act as a field-informed voice into Product and Engineering, surfacing real-world technical friction.

• Serve as a subject matter expert for non-support technical questions that exceed standard documentation.

• Provide architectural guidance across:

  • Secure build pipelines

  • Software supply chain integrity

  • Container security and governance

  • AI/ML workload governance (where applicable)

  • AI agent architecture patterns: isolated execution environments, MCP policy enforcement, model artifact provenance

• Partner with Sales Engineers and Post-Sales teams to ensure technical continuity without owning deal cycles.

You are a deeply technical practitioner who enjoys teaching, systematizing expertise, and scaling architectural excellence across customer populations. You prefer building reusable technical systems over repetitive 1:1 firefighting, but can step into consultative workshops when required.

• 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.

• Ability to present complex technical topics clearly to senior engineering audiences.

• Strong written communication skills; experience producing technical blogs or deep technical content.

• Hands-on experience with AI/ML development workflows, including model packaging, dependency management, reproducibility, and governance considerations within containerized environments.

• Practical Experience with AI coding agent runtimes and sandboxed execution environments (e.g., agent isolation, MCP tool governance)

• Familiarity with Docker SBX and MCP Gateway as enterprise controls for agentic AI workloads

• Familiarity with secure software supply chain practices, including SBOM generation and consumption, artifact signing, provenance (e.g., SLSA concepts), vulnerability management, and policy enforcement.

• Deep understanding of the container image lifecycle, including build optimization, image hardening, base image strategy, registry governance, promotion workflows, and lifecycle management from development through production.

• Practical experience implementing or advising on Secure Software Development Lifecycle (SSDLC) practices, including secure build pipelines, policy-as-code, compliance controls, and DevSecOps integration.

• Exposure to governance frameworks or regulatory models impacting modern development environments (e.g., NIST guidance, EU AI Act, internal enterprise policy frameworks).

• Experience designing reusable lab environments, demo frameworks, or reference architectures for engineering audiences.

• Background in Platform Engineering, DevSecOps, or Security Architecture roles where architectural decisions directly influenced developer experience and risk posture.

• Clear map of recurring advanced technical questions.

• Identified priority PoC/use-case patterns to formalize.

• Proposed first scalable technical asset or session outline.

• At least one repeatable enablement session running.

• One codified PoC pattern reusable across customer cohorts.

• Measurable reduction in repeated advanced technical questions in a target area.

• Demonstrable lift in technical adoption across a defined customer cohort.

• Library of scalable technical assets supporting key journey stages.

• Recognized internally as the go-to SME for advanced post-sales architecture questions.