Lead Engineer, Merchandise Technology - Pricing

Foot Locker•,

1d•$130,000 - $150,000•Remote

About The Position

This role is 100% REMOTE. At this time, Foot Locker will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, or another type of work authorization). We are seeking a highly capable Lead Engineer to drive delivery and technical execution across global merchandising technology platforms. This role is responsible for leading engineering efforts, guiding solution implementation, and ensuring high-quality delivery across merchandising domains. This role operates across both legacy and modern platforms, supporting current systems while driving modernization, reducing technical debt, and enabling transition to scalable, cloud-based solutions. The role operates within a complex global business model spanning multiple regions and supports a distributed delivery organization, including offshore engineering teams.

Requirements

Bachelor’s degree in Computer Science, Engineering, or related field
7–10+ years of experience building and supporting enterprise applications
Strong experience with modern application development (APIs, microservices, cloud platforms)
Experience working across legacy and modern systems, including modernization efforts
Experience leading engineering teams or technical initiatives
Strong understanding of integration patterns and distributed systems
Experience working in global, distributed teams including offshore models
Strong problem-solving, communication, and leadership skills

Nice To Haves

Experience designing or implementing AI/ML-enabled solutions in enterprise systems preferred

Responsibilities

Lead design, development, and implementation of solutions aligned with business and architectural standards
Own delivery of features, enhancements, integrations, and defect resolution across platforms
Drive adoption of modern engineering practices including API-first, event-driven, and cloud-native approaches
Lead implementation of intelligent and data-driven solutions, including integration of AI/ML capabilities into applications and workflows
Evaluate and apply tools such as Copilot and other AI-assisted development technologies to improve engineering productivity and quality
Ensure solutions meet requirements for performance, scalability, and reliability
Lead engineering across merchandising capabilities, which may include: Planning (allocation, assortment, MFP), Pricing, promotion, and markdown, Core merchandising and item/product systems, Inventory, replenishment, and size/pack optimization
Support and enhance legacy platforms while contributing to modernization and simplification efforts
Support and enable advanced capabilities through data and AI-driven solutions
Ensure data accuracy and operational integrity across systems
Drive adherence to engineering standards, coding best practices, and architecture guidelines
Guide teams in selecting appropriate technologies across a polyglot environment, balancing business needs, system constraints, and long-term scalability
Lead code reviews and design reviews to ensure quality and consistency
Improve system performance, scalability, and maintainability
Contribute to CI/CD pipelines, automation, and DevOps practices
Lead and mentor engineers, providing technical guidance and coaching
Coordinate work across onshore and offshore teams to deliver against shared goals
Support agile delivery practices including backlog management, estimation, and sprint execution
Act as a technical lead on cross-functional initiatives
Partner with Solution Architects to ensure designs are practical and executable
Provide feedback to influence architectural decisions based on implementation realities
Collaborate with product, business, and data teams to align on requirements and delivery
Identify opportunities to improve systems, reduce complexity, and eliminate technical debt
Contribute to modernization initiatives including migration, refactoring, or replacement of legacy applications
Evaluate and apply new technologies and tools to improve engineering outcomes