Senior Software Engineer

Senior Software Engineer - Data and AI Platforms

Business Unit:

Store Support Centre (SSC) Time Type:

Full-time Description & Requirements

Who we are

lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people. About this team

The Enterprise Data & AI team is a strategic and operational driver of growth for lululemon, owning and building the data and AI platforms and products that enable the enterprise to operate with intelligence at scale. The team leads the design and delivery of a trusted unified data foundation, advanced analytics capabilities, and AI solutions across lululemon’s vertically integrated retail ecosystem, embedding strong data governance and responsible AI practices from the very beginning. By applying AI to critical business challenges and creating new, transformative AI solutions, the team helps reshape how lululemon operates. Through deep partnership with product, technology, and business teams, Enterprise Data & AI accelerates product innovation, unlocks measurable value, elevates guest and educator experiences, and drives enterprise efficiency. Core responsibilities

As a Senior Software Engineer, you will design and build data systems, AI-enabled platform capabilities, and enterprise solutions that support multiple product teams, contributing to architectural patterns for how enterprise knowledge is modeled, connected, and consumed. You will work at the intersection of Data (logical and semantic), AI/LLM retrieval and grounding, and distributed systems and APIs. You will drive technical decisions with broad impact across multiple teams including architecture patterns and technology selections, conduct high-impact code reviews focusing on system design and long-term maintainability, and establish engineering standards and best practices adopted across the domain including testing strategies and deployment procedures. You will mentor engineers at multiple levels providing guidance on advanced technical concepts and career development, partner with product and business stakeholders on technical strategy and roadmap planning, and represent engineering perspective in cross-functional initiatives while leading incident response for critical production issues. This role may require availability outside of standard business hours, including on call support, based on business needs. Select responsibilities include:

Contribute to and help evolve canonical semantic models (taxonomies, ontologies, knowledge graphs) for enterprise domains such as product, customer, and supply chain Build and maintain systems that provide high-quality context for LLMs, including Retrieval pipelines (RAG / GraphRAG), Semantic search (embeddings, hybrid search), and evidence-based reasoning layers Collaborate with AI/ML Science teams to validate model correctness, reduce hallucination risk, and improve trust in AI-generated outputs Identify and address challenges of data ambiguity, duplication, and inconsistencies through data validation, schema governance, and versioning practices Lead implementation of complex systems and features spanning multiple services within established architectural frameworks and make decisions with minimal supervision Write exemplary code demonstrating engineering best practices in critical systems as technical reference for teams Establish and enforce coding standards, testing practices, and engineering best practices across multiple teams in domain Provide technical input and implementation perspectives to architects on system design and integration approaches Lead code quality and design reviews across teams ensuring technical alignment with organizational standards Qualifications

Bachelor’s degree in Computer Science, Software Engineering, or related technical field; Master’s degree beneficial, or equivalent experience 6-10 years of software development experience, building complex systems and driving technical initiatives across teams, or equivalent Proven track record of writing exemplary code that serves as a technical reference; experience establishing coding standards and quality practices adopted across a domain Demonstrated ability to decompose highly complex problems including algorithmic challenges into scalable solutions; deep understanding of system-wide implications of technical decisions across multiple services E