Job description

The Senior Manager, Store Systems Software leads a technical team designing and developing the applications used by store associates across 2,000+ retail locations. You will own team performance, delivery, and quality while partnering closely with business stakeholders and cross-functional IT groups. Beyond traditional delivery management, this role is expected to lead an AI-forward, quality-engineered, metrics-driven software organization — championing modern agile practice, automated testing, and the responsible adoption of AI-assisted and agentic development tooling to raise both velocity and quality. This position sits onsite 5 days a week in Grapevine, TX. What You'll Lead Delivery & Engineering Leadership • Establish and monitor project objectives, resource leveling, timelines, milestones, and deadlines, ensuring deliverables are met on schedule, accepted by customers, and transitioned smoothly to operational status. • Work with business partners to clarify, scope, and prioritize requests for enhancements and modifications. • Manage the full software development lifecycle and technical risks across all projects, inclusive of ongoing operational costs. • Ensure cross-functional communication and alignment across IT, security, product, and store-operations teams. • Identify opportunities for improvement, make constructive recommendations for change, and stay at the leading edge of evolving industry standards and practices. AI-Forward Engineering • Champion adoption of AI-assisted development and agentic tooling (e.g., GitHub Copilot, Claude Code, LLM-based code review and test generation) across the team. • Establish governance, quality guardrails, and security controls so AI accelerates delivery without degrading code quality, IP integrity, or compliance. • Define productivity baselines and measure the real impact of AI tooling on throughput, quality, and developer experience. • Evaluate and pilot emerging AI/agentic capabilities for store-systems use cases, balancing innovation with operational risk. Quality & Test Automation • Own a shift-left quality strategy: automated unit, integration, and regression testing embedded directly in CI/CD pipelines. • Define and enforce coverage, reliability, and quality-gate thresholds; hold the line on quality as AI increases commit velocity. • Ensure all projects meet GameStop security requirements and automated testing standards prior to release. • Leverage AI-augmented test generation to expand coverage and catch edge cases without sacrificing speed. Agile Practice & Engineering Effectiveness • Act as a fluent agile practitioner and coach — facilitating Scrum/Kanban (or SAFe) practices, removing impediments, and driving continuous improvement. • Instrument and improve engineering effectiveness using DORA metrics (deployment frequency, lead time for change, change-failure rate, MTTR) and flow metrics (velocity, cycle time). • Create and sustain a work environment that balances entrepreneurial thinking with disciplined risk management. People Leadership • Demonstrate the core leadership behaviors expected at GameStop — strong results orientation, bias for action, high emotional intelligence, maturity, and professionalism. Foster a culture of constructive feedback, a high service mindset, and a commitment to respectful, inclusive, ethical collaboration. • Actively build the capability of others through relevant, timely, balanced feedback; coaching and teaching; encouraging mentoring relationships; and using recognition and rewards to reinforce desirable behaviors. • Coach, develop, retain, train, hire, and, when needed, discipline team members to build and maintain a high-performing team. Required Qualifications: • Bachelor's degree in Information Systems, Computer Science, or a related field — or equivalent year-for-year experience. • 3+ years directly managing software engineering teams, with proven excellence in team performance and project outcomes. • Fluent agile practitioner — 3+ years actively leading Scrum/Kanban (or SAFe) teams, using agile metrics to drive predictable, continuously improving delivery. • Demonstrated experience leading teams that build and deliver applications on contemporary front-end and back-end technologies, including cloud platforms (AWS, Azure, or Google Cloud), Kubernetes, microservices, and service-oriented architecture. • Hands-on experience establishing test automation and CI/CD quality gates (e.g., Selenium, Playwright, pytest, or similar), with TDD/ATDD and automated regression practices. • Working familiarity with AI-assisted development tooling and a clear point of view on how to adopt it responsibly at team scale. • Strong project-planning skills with the ability to organize, prioritize, and manage responsibilities under tight deadlines in fast-paced, multi-priority environments. • Proven ability to remain composed, flexible, and productive amid changing priorities and high-stress situations. • Excellent written and spoken English, including the ability to deliver clear, constructive feedback. Preferred Qualifications: • Hands-on Python experience in practical development environments. • Experience deploying agentic AI or established AI/ML toolsets at enterprise scale. • Familiarity with DevSecOps practices and engineering-effectiveness platforms / DORA dashboards. • Proven leadership of cross-functional teams comprising developers and project managers. • Knowledge of retail systems and processes. • Commitment to GameStop policies and procedures, including attendance, confidentiality, conflict of interest, and ethical responsibilities.

Requirements

Must-haves

This position sits onsite 5 days a week in Grapevine, TX.
What You'll Lead
Delivery & Engineering Leadership
Establish and monitor project objectives, resource leveling, timelines, milestones, and deadlines, ensuring deliverables are met on schedule, accepted by customers, and transitioned smoothly to operational status.
Work with business partners to clarify, scope, and prioritize requests for enhancements and modifications.
Manage the full software development lifecycle and technical risks across all projects, inclusive of ongoing operational costs.
Ensure cross-functional communication and alignment across IT, security, product, and store-operations teams.
Identify opportunities for improvement, make constructive recommendations for change, and stay at the leading edge of evolving industry standards and practices.
AI-Forward Engineering
Champion adoption of AI-assisted development and agentic tooling (e.g., GitHub Copilot, Claude Code, LLM-based code review and test generation) across the team.
Establish governance, quality guardrails, and security controls so AI accelerates delivery without degrading code quality, IP integrity, or compliance.
Define productivity baselines and measure the real impact of AI tooling on throughput, quality, and developer experience.
Evaluate and pilot emerging AI/agentic capabilities for store-systems use cases, balancing innovation with operational risk.
Quality & Test Automation
Own a shift-left quality strategy: automated unit, integration, and regression testing embedded directly in CI/CD pipelines.
Define and enforce coverage, reliability, and quality-gate thresholds; hold the line on quality as AI increases commit velocity.
Ensure all projects meet GameStop security requirements and automated testing standards prior to release.
Leverage AI-augmented test generation to expand coverage and catch edge cases without sacrificing speed.

Nice-to-haves

Hands-on Python experience in practical development environments.
Experience deploying agentic AI or established AI/ML toolsets at enterprise scale.
Familiarity with DevSecOps practices and engineering-effectiveness platforms / DORA dashboards.
Proven leadership of cross-functional teams comprising developers and project managers.
Knowledge of retail systems and processes.
Commitment to GameStop policies and procedures, including attendance, confidentiality, conflict of interest, and ethical responsibilities.

Application prep

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Keywords to mirror

aiagilellmci/cdscrumawsazurekubernetespythonml

Platform: ukg
Effort: medium