Senior Software Engineer - Data and AI Platforms

lululemon; Vancouver; On-site; CAD 133,000 - 174,000; Full time

Benefits offered by this job

Extended health

Dental benefits

Paid time off

Retirement plan matching

Parental top-up

Career development

Mentorship

Wellbeing programs

Job summary

lululemon Athletica Inc. in Canada is seeking a Senior Software Engineer for Data and AI Platforms to join the Enterprise Data & AI team.

You will design and build data systems and AI-enabled capabilities across product teams, shaping enterprise data foundations and scalable solutions. The role requires 6–10 years of software development experience, a strong record of coding quality, and the ability to drive architectural decisions.

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
• Experience designing integration solutions for complex domain areas; track record of driving integration implementation decisions across teams within architectural standards
• Experience building knowledge bases in retail or similar domains
• Familiarity with search, recommender and RAG/GraphRAG hybrid retrieval architectures
• Experience defining enterprise semantic layers used across multiple product teams
• Exposure to AI-Driven systems – optimization, predictions and Agents
• Experience working with knowledge representation for LLM-powered applications

Responsibilities

• The role will design and build data systems, AI-enabled platform capabilities, and enterprise solutions across product teams
• Drive architectural patterns and technology choices with broad impact
• Lead code reviews and establish engineering standards and testing strategies
• Mentor engineers and collaborate with product and business stakeholders on technical strategy
• Lead incident response for critical production issues
• Work onsite four days per week at minimum
• Contribute to canonical semantic models and knowledge graphs
• Maintain high-quality context for LLMs and retrieval pipelines

Skills

Software development

System architecture

AI/ML knowledge

Code quality practices

Integration design

Education

Bachelor's degree in Computer Science or related field

Tools

Retrieval pipelines (RAG)

Semantic search

GraphRAG

Job description

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
• Experience designing integration solutions for complex domain areas; track record of driving integration implementation decisions across teams within architectural standards
• Experience building knowledge bases in retail or similar domains
• Familiarity with search, recommender and RAG/GraphRAG hybrid retrieval architectures
• Experience defining enterprise semantic layers used across multiple product teams
• Exposure to AI-Driven systems – optimization, predictions and Agents
• Experience working with knowledge representation for LLM-powered applications

additional notes

Authorization to work in Canada is required for this role.

compensation and benefits package

lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and teamperformance. Thetypical hiring range for this positionis from $132,600 - $174,000annually ; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program, subject to program eligibility requirements.

At lululemon, investing in our people is a top priority. We believe that when life works, work works. We strive to be the place where inclusive leaders come to develop and enable all to be well. Recognizing our teams for their performance and dedication, other components of our total rewards offerings include support of career development, wellbeing, and personal growth:

• Extended health and dental benefits, and mental health plans
• Paid time off
• Savings and retirement plan matching
• Parenthood top-up
• Extensive catalog of development course offerings
• People networks, mentorship programs, and leadership series (to name a few)

Note: The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice.

workplace arrangement

In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.

Only those applicants under consideration will be contacted. Please accept our utmost appreciation for your interest. Lululemon is an Equal Employment Opportunity employer. Employment decisions are based on merit and business needs, and not on race, color, creed, age, sex, gender, sexual orientation, national origin, religion, marital status, medical condition, physical or mental disability, military service, pregnancy, childbirth and related medical conditions or any other classification protected by federal, state or provincial and local laws and ordinances. Reasonable accommodation is available for qualified individuals with disabilities, upon request. This Equal Employment Opportunity policy applies to all practices relating to recruitment and hiring, compensation, benefits, discipline, transfer, termination and all other terms and conditions of employment. While management is primarily responsible for seeing that Lululemon equal employment opportunity policies are implemented, you share in the responsibility for assuring that, by your personal actions, the policies are effective.

lululemon is committed to providing reasonable accommodation to applicants with disabilities. If you would like someone from our team to contact you for individualized support, email us at [e-mail] . In your email, please include the position title, the location of the position and the nature of your request.

The use of AI tools, including but not limited to ChatGPT, Microsoft Copilot, Gemini, DeepSeek, or any other AI-assisted software, is strictly prohibited during the interview process. This includes, AI-generated responses, content creation, or any form of automated assistance in live interviews, case studies, technical assessments, or written submissions.

At lululemon, we are committed to privacy, integrity, transparency, and ethical hiring practices. Our commitment to responsible AI ensures that proprietary information is protected and that all hiring decisions are based on an individual’s own skills, judgment, and expertise without AI assistance. Any use of AI during the interview process will result in immediate disqualification. lululemon reserves the right to use AI detection tools to verify the authenticity of candidate responses.