Director, Software Engineering: Retail Platform Delivery (ELERA)

Toshiba Global Commerce Solutions - External•Durham, NC

16h

About The Position

Toshiba Global Commerce Solutions is hiring a Director of Software Engineering 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. This is not an engineering-only or QA-only role. You own the outcome, the telemetry that proves it, and the workflows that compound it.

Requirements

12+ years in software engineering
6+ years leading engineering organizations at scale (100+ engineers)
Proven ownership of production systems serving Fortune 500 customers
Delivered complex, distributed, multi-tenant platforms under strict SLOs
Direct customer-facing engineering leadership at executive level
Distributed systems, event-driven architectures, microservices, API design
Cloud-native (AWS, Azure, or GCP) AND edge/store deployment models
Observability engineering: OpenTelemetry, SLOs, structured logging, distributed tracing
Progressive delivery: feature flags, canary, blue/green, shadow traffic
CI/CD at scale, GitOps, supply chain security
Performance engineering: load, stress, endurance, chaos
Modern quality practices: TDD, contract testing, mutation testing
Hands-on experience with LLM-based engineering tooling (Claude Code, agentic IDE plugins, MCP servers)
Working understanding of agent orchestration, MCP, and RAG architectures
Ability to design AI-leveraged workflows that compound team output, not just assist individuals
Comfortable measuring AI leverage in dollar-equivalent and headcount-equivalent terms
Executive customer-facing credibility; holds the room with CIOs and CTOs
Decides under ambiguity with clear tradeoff articulation
Balances speed vs quality, customization vs platform integrity, innovation vs stability
Execution-focused, data-driven, low tolerance for process theater

Nice To Haves

Retail domain: POS, payments, loyalty, store systems, edge computing at store
ELERA platform familiarity or comparable enterprise retail platform experience
Background spanning both engineering AND quality disciplines
PCI DSS and SOX compliance experience in a payments context

Responsibilities

Customer-Facing Engineering Leadership
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
End-to-End Delivery Ownership (DORA-Native)
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
Unified Engineering + Quality Model
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
AI-Native Development (Agentic Delivery)
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, CloudOps 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
Scalability, Performance, and Reliability (SRE Discipline)
SLOs and error budgets defined for every customer-facing service; error budget exhaustion blocks feature work
Observability-as-code: OpenTelemetry 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 exponential backoff and jitter; blue/green at the edge
Horizontal scale to tens of thousands of lanes across multi-tenant, multi-region deployments
Capacity planning tied to FinOps: cost per transaction tracked and optimized, not assumed
Platform Engineering & Developer Experience
Treat the engineering org as the customer of an internal developer platform (AI Dev Portal as the front door)
Golden paths: paved roads for new services, standard observability, standard security posture, standard CI/CD
Self-service environments: CloudOps Sandbox, on-demand synthetic test data, ephemeral preview environments per PR
Developer productivity instrumented: DORA plus SPACE metrics; time-to-first-commit for new hires; PR review latency; local build time
Professional Services Engineering Model
Customer-specific extensions delivered without fragmenting the platform
Config-driven first, code-driven by exception. Every bespoke extension has a sunset plan or a promotion path to core.
Reusable solution accelerators for common retail integrations (payments, peripherals, back office, tax, loyalty, CRM)
Integration contracts versioned and governed; breaking changes require deprecation windows and migration tooling
Clear engineering handoff to customer operations and support, with runbooks, dashboards, and on-call rotations live at go-live
Release Governance and Operational Readiness
Engineering-driven release gates, not process theater:
Functional completeness, validated by automated acceptance
Performance validation against published SLOs
Integration stability, with contract tests green
Observability live (dashboards, alerts, runbooks) before traffic
Security posture verified (SAST, DAST, SCA, SBOM, secrets scanning, threat model reviewed)
Rollback tested, not assumed
Post-release: automated canary analysis, 24-hour watch, blameless incident reviews with 48-hour turnaround and action-items tracked to closure
Security and Compliance Engineering
Shift-left security: threat modeling at design time, SAST in every PR, DAST in staging
Compliance built into the pipeline: PCI DSS, SOX, GDPR controls are code, not audit artifacts
Software supply chain: SBOM generation, signed artifacts, SLSA build-level targets
Secrets management, zero-trust service-to-service authentication, least-privilege IAM
Leadership and Organizational Impact
Lead cross-functional teams spanning Engineering, embedded Quality, and Professional Services
Develop engineering leaders who:
Own outcomes, not tasks
Think in systems and data, not features
Hold the room at the customer executive table
Drive a culture of:
Accountability without blame
Evidence-based decisions (telemetry, metrics, experiments)
Continuous improvement with measurable deltas