We are seeking a
Senior Engineering Manager to lead Store Systems Software while helping the organization adopt AI tools and capabilities. The current environment is early in its AI journey, with a strong foundation in cloud, Agile delivery, and enterprise retail systems. This role will introduce AI incrementally, focusing on developer productivity, operational efficiency while ensuring solutions remain secure, compliant, reliable, and aligned with business priorities. The Senior Engineering Manager operates independently, leading teams responsible for applications used by store associates across 1,500+ retail locations, while partnering closely with business stakeholders and cross-functional IT teams.
This position sits onsite 5 days a week in Grapevine, TX.
Key ResponsibilitiesAI Enablement
- Serve as a hands-on leader and guide for the organization's AI adoption efforts, helping teams move from experimentation to production-ready use cases.
- Identify practical, low-risk opportunities to apply AI, such as:
- AI-assisted development and testing
- Intelligent operational insights
- Automation for support, reporting, or internal workflows
- Lead proofs of concept and pilots, clearly measuring value, cost, and impact before scaling.
- Partner with Security, Legal, and IT leadership to ensure AI usage aligns with company policies, data protection, and ethical standards.
- Educate engineers and stakeholders on what AI can-and cannot-do, setting realistic expectations and building confidence.
Store Systems & Enterprise Delivery
- Lead development of applications used daily by store associates across 1,500+ retail locations.
- Establish and monitor project objectives, timelines, resourcing plans, milestones, and deliverables, ensuring commitments are met.
- Collaborate with business partners to clarify, scope, and prioritize enhancements, including where AI may or may not be appropriate.
- Manage the full software development lifecycle, including technical risk, testing, security, operational readiness, and ongoing support.
- Ensure all systems meet enterprise security, quality, and compliance standards prior to release.
Engineering Management & Change Leadership
- Lead and develop Agile engineering teams, with an emphasis on coaching through change as new tools and practices are introduced.
- Build trust by balancing innovation with stability, especially in store-critical systems.
- Actively develop talent through:
- Timely, balanced feedback
- Coaching and mentoring
- Clear performance expectations and recognition
- Foster a culture of:
- Results orientation and bias for action
- High emotional intelligence and professionalism
- Psychological safety, inclusion, and continuous learning
Process, Agile & Operational Excellence
- Strengthen Agile practices to support predictable delivery in fast-paced, multi-priority environments.
- Help teams remain composed and effective in high-pressure operational scenarios, setting a calm, solution-oriented tone.
- Identify opportunities to improve processes, tooling, and workflows, including selective use of AI where it improves efficiency without increasing risk.
- Balance entrepreneurial thinking with disciplined risk management, particularly when piloting new technologies.
Required QualificationsLeadership & Experience
- Bachelor's degree in Computer Science, Information Systems, or related field (or equivalent experience).
- 10+ years of direct experience managing Agile software development teams.
- Proven ability to hire, coach, develop, and retain high-performing teams.
- Experience leading cross-functional initiatives involving developers, project managers, and business stakeholders.
Technical & AI-Readiness Skills
- Experience delivering applications using modern front-end and back-end technologies, including:
- Cloud platforms (AWS, Azure, or Google Cloud)
- Kubernetes and service-oriented architectures
- Solid hands-on experience with Python in practical development environments (preferred).
- Exposure to or interest in AI and GenAI tools, with the ability to:
- Evaluate tools critically
- Run small-scale experiments
- Translate outcomes into business-relevant applications
- Strong understanding of system reliability, security, and operational support.
Preferred Qualifications- Experience working in retail systems or store operations environments.
- Prior involvement in AI adoption, platform modernization, or developer tooling transformation.
- Ability to act as a translator between technical teams and non-technical business leaders.
What Success Looks Like- AI is introduced incrementally and responsibly.
- Engineering teams adopt new tools with clarity, confidence, and guardrails.
- Store systems remain stable, secure, and reliable, even as innovation increases.
- Business stakeholders see measurable value from AI without inflated expectations.
- The organization moves from "AI curiosity" to "AI capability" in a sustainable way.
