Principal Software Engineer, Developer Platform

Toshiba Global Commerce Solutions is seeking a Principal Software Engineer, Developer Experience Platform to build and operate the engineering system that moves work from requirement through local development, focused validation, CI/CD, deployment, and production feedback across a mature retail point-of-sale estate.

This is not an advisory architecture role. You will work directly in Java and JavaScript repositories, Maven builds, Docker and Kubernetes environments, Git Lab/Jenkins pipelines, platform services, and Open Telemetry traces. You will reproduce developer friction, write the critical code, and own improvements through rollout and adoption.

You will also direct agentic engineering workers, AI coding and analysis agents that execute bounded engineering tasks. You will supply context and constraints, decompose work, supervise execution, review and correct output, enforce deterministic gates, and remain accountable for every accepted change.

Developer Experience is treated as an engineering product, not a collection of tools. Success means engineers can onboard, build, test, provision, deploy, diagnose, and learn from production with less waiting, less cognitive load, and fewer manual handoffs.

Build a developer platform and agentic engineering operating model that lets engineers move from requirement to safe production feedback with less waiting, cognitive load, and manual coordination. Success is demonstrated through working software, faster feedback, reliable self-service, and sustained adoption, not through the volume of diagrams or standards produced.

• A mature POS estate spanning Java and JavaScript applications, Maven builds, Docker-based local and CI environments, Kubernetes and Helm deployment assets, and Git Lab/Jenkins delivery workflows.
• Cloud and store-edge software with different connectivity, rollout, recovery, security, and operational constraints.
• A large business-facing Cucumber BDD suite with browser-driven validation, seeded test data, service dependencies, parallel execution, and release-gating implications.
• Existing Open Telemetry -based diagnostics and an evolving browser-automation path that must be integrated into useful developer feedback rather than operated as isolated tooling.
• An expanding agentic engineering model in which AI workersassistwith analysis, implementation, testing, review, triage, and release preparation under controlled access and deterministic validation.

• Personally build andoperatedeveloper-facing services, command-line tools, integrations, templates, reusable pipeline libraries, portal or catalog capabilities, and environment automation.
• Use profiling, logs, metrics, traces, and controlled experiments to reproduce bottlenecks andeliminateroot causes across local, CI, environment, deployment, and production-feedback workflows.
• Carrycritical changes from design through code, migration, deployment, runbooks, adoption, and operational follow-through. A recommendation is not complete until the path works for engineers.

• Map the end-to-end developer journey,identify the highest-cost friction, maintain a prioritized improvement roadmap, and publish clear ownership and service expectations.
• Use developer research, workflow telemetry, support demand, and delivery data to distinguish systemic constraints from isolated preferences.
• Maintain platform contracts, lifecycle policies, deprecation paths, and architecture decisions that are backed by working reference implementations and practical migration plans.

• Create reproducible, automated setup for source access, dependencies, configuration, secrets, local services, test data, and development environments.
• Improve edit-build-test-debug cycles through caching, incremental execution, targeted validation, realistic mocks or service virtualization, and actionable local diagnostics.
• Replace tribal knowledge with executable documentation, ownership metadata, runbooks, and self-service guidance thatremainscurrent because it is part of the delivery system.

• Define paved roads for services, APIs, user interfaces, data and configuration, security, observability, testing, deployment, and store-edge components.
• Build and govern templates, scaffolding, reusable libraries, pipeline components, policy automation, and a developer portal or catalog that exposes ownership, documentation, dependencies, health, and support paths.
• Enable on-demand and epithelial environments, preview environments, seeded or synthetic test data, automated access, and lifecycle cleanup through infrastructure ascode.

• Engineer and evolve developer-facing Git Lab/Jenkins workflows that provide fast, tiered feedback for local changes, merge requests, integration, release qualification, deployment, and…