Sr. Manager, AI & Automation

Foot Locker•UNAVAILABLE, UNAVAILABLE

1d•Remote

About The Position

Foot Locker, Inc. is seeking an experienced technology leader to build and run the engineering team delivering Generative AI, Agentic AI, and intelligent automation products across the retail enterprise. The role owns delivery, reliability, governance, and cost for the AI and automation portfolio, partnering with architecture, data, product, and business leaders to turn enterprise AI strategy into production capabilities for Merchandising, Supply Chain, Stores, Digital Commerce, Finance, Customer, and Corporate functions. The Sr. Manager leads engineers, senior engineers, and contract resources; establishes the team’s operating model, hiring plan, and engineering standards; and is accountable for what the team delivers. The role owns people, delivery, and operating model across the portfolio rather than any single system. It sets priorities with product and business partners and makes staffing, sequencing, and build-versus-buy decisions within enterprise architecture standards set by the Sr. Architect, AI & Automation. The team’s AI products are used by store, merchandising, supply chain, digital commerce, and corporate teams across Foot Locker’s brands and digital channels. This role is 100% remote and US-based. Foot Locker will not sponsor new employment authorization or offer immigration-related support for this position.

Requirements

At least 7 years of experience in software engineering, data engineering, applied AI, automation, or related technology areas.
At least 3 years of direct people leadership, including hiring, coaching, performance management, and developing engineers across levels.
Demonstrated track record of delivering production technology products at enterprise scale, rather than proofs of concept.
Working technical depth in Generative AI, LLMs, Agentic AI, RAG, embeddings, vector search, prompt engineering, and AI orchestration sufficient to lead design reviews, challenge technical choices, and earn senior engineers’ trust.
Familiarity with Python, SQL, REST APIs, cloud architecture, and modern data platforms such as Snowflake and Databricks.
Experience with LLMOps, CI/CD, evaluation frameworks, AI observability, and production monitoring.
Strong understanding of Responsible AI, data governance, security, privacy, RBAC, and regulatory compliance in an enterprise environment.
Ability to own budgets, vendor relationships, consumption forecasting, and cost management for a technology portfolio.
Experience leading distributed and blended teams, including onshore, offshore, and contract resources.
Excellent written and verbal communication skills, with the ability to influence engineering teams, business stakeholders, directors, and executive leadership.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, and 7 or more years of related experience and/or training, or an equivalent combination of education and experience.
Ability to communicate clearly, interpret communications, write management reports and professional correspondence, and speak effectively with peers, management, customers, and associates.
Ability to plan and execute unusual and difficult work, take initiative, make decisions when appropriate, solve practical and nonstandard problems, interpret varied instructions, and deal constructively with conflict.
High motivation, exceptional attention to detail, ability to derive answers from communications across the business, teamwork, and flexibility to support varied department goals.

Nice To Haves

Experience in Retail, Digital Commerce, Supply Chain, or Customer Analytics.
Experience working in Agile product delivery environments.
Experience with Azure OpenAI, Snowflake Cortex AI, Databricks, the Microsoft Copilot ecosystem, Power BI/Fabric, AI gateways, and Model Context Protocol (MCP), or equivalent technologies.
Experience establishing a new AI or automation capability from initial team formation through sustained production operation.
Experience managing managers or technical leads.
Public cloud experience, preferably Azure or AWS.
Previous experience at a Fortune 500 company.
Comfort operating with ambiguity and setting direction before standards are fully defined.

Responsibilities

Hire, coach, and develop AI and automation engineers; set expectations, conduct performance and career conversations, and build a durable team bench across levels.
Own the roadmap, commitments, and end-to-end delivery of AI agents, RAG solutions, automation workflows, APIs, and enterprise integrations.
Define how work enters the team, how priorities are set, and how capacity is allocated across PODs, business domains, and shared platform work.
Establish and enforce standards for code quality, testing, evaluation, documentation, security, observability, and operational readiness.
Own reliability, incident response, service levels, and remediation for AI and automation solutions in production.
Require measurable evaluation of AI capabilities before and after release, including groundedness, retrieval quality, task success, latency, and cost per task.
Forecast and manage token, compute, platform, and licensing spend, and improve unit costs as usage scales.
Operationalize Responsible AI, security, privacy, PII protection, RBAC, model and prompt governance, and audit readiness with Security, Legal, and Risk.
Translate enterprise AI reference architectures and guardrails into implementations and feed production learning back into standards.
Partner with business and product leaders to shape demand, define measurable outcomes, and communicate trade-offs, sequencing, and capacity constraints.
Evaluate AI platforms, models, and vendors; manage contracts, renewals, consumption commitments, and partner performance.
Promote reusable services, agents, skills, connectors, and accelerators to reduce the cost of delivering future use cases.
Report portfolio health, risk, adoption, and value realization to directors and executive leadership.
Oversee hiring, onboarding, goal setting, coaching, performance management, career development, and resource planning for engineers, senior engineers, and contract resources.