Director, Software Engineering: Retail Platform Delivery; ELERA)

Must be located near or within the area of Cincinnati, Ohio.

Toshiba Global Commerce Solutions is seeking a Director, Software Engineering:
Retail Platform Delivery (ELERA) to own end-to-end delivery of the ELERA retail platform across our strategic global retail partners, including Fortune 100 grocery, warehouse club, and general merchandise accounts.

This role collapses Development, Test, and Professional Services Engineering into a single accountable function and operates as the customer-facing engineering authority for strategic programs. You own what ships, how it scales, how it recovers, and how quickly the team learns.

This role runs on Toshiba's agentic AI development ecosystem as the default way of working, not a side experiment. Agents participate in requirement decomposition, code generation, test authoring, PR review, defect triage, and release scoring. You are expected to measure and compound that leverage.

• Delivery velocity AND production reliability (DORA metrics with published targets)
• Unified engineering and quality accountability in one org
• Customer-facing technical authority for strategic retail accounts
• AI-native development workflows that compound team output quarter over quarter
• Production outcomes: what ships, how it performs, how it recovers, what it costs to run

Primary engineering authority for customer programs spanning POS, payments, loyalty, and store systems

Partner with customer leaders to define success criteria, operational acceptance, rollout strategy, and risk posture

Translate real-world retail workflows into architecture decisions, API contracts, and system behavior

Maintain architecture decision records (ADRs) and a visible technical debt register tied to delivery plans

Own the four DORA metrics as published, measurable targets:

• Deployment Frequency: on-demand for services, scheduled-safe for store edge
• Lead Time for Changes: under 24 hours for services
• Change Failure Rate: under 10% trending down
• MTTR: under 1 hour for customer-impacting incidents

AI-built feature branches with pre-merge release testing: agents build the full feature on an isolated branch; release-grade testing (functional, performance, security, integration) runs on that branch and must pass before merge. Main stays releasable at all times.

Progressive delivery is mandatory: feature flags, canary, blue/green, shadow traffic. Decouple deploy from release.

Zero scheduled-downtime windows for cloud services; store edge deploys are non-disruptive to live lanes

Test-Driven Development is the baseline. Tests exist before code. No exceptions for new code paths.

Quality gates block merges: coverage thresholds, mutation score, static analysis, SAST, dependency and license scanning, SBOM generation

Contract testing (consumer-driven) between every service boundary;
OpenAPI and AsyncAPI versioned and governed

Chaos engineering in staging, quarterly game days, production-like load testing ahead of peak retail events

Shift-right validation: synthetic monitoring, canary analysis, error budget enforcement

Own metrics: defect leakage, change failure rate, cycle time, escape rate, production incident rate

Leverage Toshiba's agentic development ecosystem as the default delivery model:

AI-assisted engineering: requirement decomposition, design-to-code, test generation, refactoring at scale, PR review

Agent-driven workflows: defect triage and clustering, root cause analysis from telemetry, release readiness scoring, customer-reported incident classification

MCP-integrated tooling: every engineer works with context-aware agents wired to source, tickets and telemetry

Agents as team members:
RaaS (RAG-as-a-Service), Sentinel AI for test authoring and execution, Agentic TPM for program management, Cloud Ops Sandbox for environment provisioning, ELERA Agent Registry for discovery

Measured leverage: agent-authored code accepted, test cases generated, incidents auto-triaged, AI-equivalent headcount by role tracked quarterly

Feedback loops: production telemetry feeds AI-ranked backlog and refactor targets

SLOs and error budgets defined for every customer-facing service; error budget exhaustion blocks feature work

Observability-as-code:
Open Telemetry instrumentation is required before merge; service.version tagged; traces, metrics, and logs correlated by default

Performance engineering: load, stress, endurance, and soak testing sized for peak retail events (Black Friday, holiday, payroll cycles)

Edge resilience: stores survive network partitions; offline transaction handling; store-and-forward retry with e