Sr. Engineer, AI & Automation

Foot Locker•,

7h•$125,000 - $155,000•Remote

About The Position

Foot Locker is seeking an experienced Sr. Engineer, AI & Automation to provide hands-on technical leadership in designing, developing, and delivering scalable AI, Generative AI, Agentic AI, and intelligent automation solutions across the retail enterprise. The role partners with architects, engineering teams, business stakeholders, and technology leaders to productionize secure, reliable, and governed AI solutions for merchandising, inventory, supply chain, store operations, digital commerce, customer experience, and enterprise analytics. The team’s AI products are used daily by store, merchandising, supply chain, digital commerce, and corporate teams across Foot Locker’s brands and digital channels. The position owns AI products and services end to end in production, including evaluation, reliability, and cost, and establishes implementation patterns for the team. It develops AI agents, RAG solutions, automation workflows, APIs, and enterprise integrations using modern cloud and data platforms. The role also establishes AI governance frameworks and transforms business processes into AI-enabled products and experiences. The role has no direct reports, but provides technical leadership, mentors engineers, and guides contract resources. This role is 100% remote and U.S.-based. Foot Locker will not sponsor a new applicant for employment authorization or offer immigration-related support for this position.

Requirements

4–7+ years of experience in software engineering, data engineering, applied AI engineering, automation, or related areas, with hands-on experience delivering AI solutions in production.
Strong experience with Python, SQL, REST APIs, JSON, and software engineering practices.
Hands-on knowledge of LLMs, GenAI, RAG, Agentic AI, embeddings, vector databases/search, and prompt engineering.
Experience with LangChain, LangGraph, Semantic Kernel, or equivalent agent/orchestration frameworks.
Experience with Azure OpenAI/OpenAI APIs or comparable enterprise LLM platforms.
Experience with Snowflake and/or Databricks and modern cloud data architectures.
Knowledge of Docker, Kubernetes, Git, CI/CD, Azure DevOps/GitHub, and Terraform.
Understanding of LLMOps, evaluation frameworks, AI observability, security, and Responsible AI.
Strong troubleshooting, problem-solving, technical leadership, and communication skills.
Bachelor’s degree from a four-year college or university, or an Associate degree in programming from a technical college, and 6 or more years of related experience and/or training, or an equivalent combination of education and experience.
Ability to communicate clearly, interpret communications, write reports and professional correspondence, and speak effectively with peers, management, customers, and other associates.
Ability to plan and execute unusual and difficult work, take initiative, solve practical and impractical problems, interpret varied instructions, and deal constructively with conflict and disagreement.
Ability to work well in a team atmosphere and be flexible in helping with a variety of department goals.
Applicants must be U.S.-based; Foot Locker will not sponsor new employment authorization or provide immigration-related support.
Candidates must keep cameras on for virtual interviews; AI tools are prohibited during interviews and assessments.

Nice To Haves

Experience in Retail, Digital Commerce, Supply Chain, or Customer Analytics domains.
Experience working in Agile product delivery environments.
Azure AI Engineer, Azure Solutions Architect, or equivalent certifications.
Experience with Snowflake Cortex AI, Databricks, the Microsoft Copilot ecosystem, Power BI/Fabric, Model Context Protocol (MCP), document AI, or equivalent technologies.
Experience with retail or supply chain systems and enterprise automation platforms.
Public cloud experience, preferably Azure or AWS.
Previous experience at a Fortune 500 company.

Responsibilities

Design and develop production-grade GenAI, Agentic AI, RAG, and automation solutions.
Build AI agents and multi-agent workflows that integrate enterprise data, APIs, applications, and business processes.
Develop RAG solutions using LLMs, embeddings, vector search, semantic retrieval, ontology and knowledge graph sources, and enterprise knowledge repositories.
Integrate AI solutions with platforms such as Snowflake, Databricks, Azure, Power BI, APIs, and retail operational systems.
Build AI-enabled solutions for retail use cases, including inventory intelligence, merchandising, supply chain, store operations, product insights, customer analytics, and business reporting.
Develop reusable AI services, APIs, frameworks, connectors, and automation components.
Implement LLMOps and CI/CD processes for automated testing, deployment, monitoring, prompt and model version management, and evaluation of groundedness, retrieval quality, task success, latency, and cost per task.
Implement AI guardrails, security, RBAC, PII protection, Responsible AI, logging, monitoring, and observability.
Optimize AI solutions for performance, scalability, reliability, token consumption, and cost.
Troubleshoot complex production issues and continuously improve AI platform capabilities.
Conduct technical reviews and mentor engineers on AI engineering and software development best practices.
Collaborate with architects to translate enterprise AI architecture and standards into production implementations.
Provide technical leadership, mentor engineers, and guide contract resources.