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Added 16 mins ago
SI
Sr. DevSecOps Cloud Specialist
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- Contract
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Added 16 mins ago
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- Contract
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Added 16 mins ago
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- Full-time
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Added 47 mins ago
O
Solution Consultant Director, Partner channel
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- Full-time
…technical excellence and team performance. The role combines senior people leadership with deep domain expertise in conversational AI, CCaaS, and enterprise sales - ensuring that the…
Added 47 mins ago
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Added 2 hours ago
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- $120,000 to $130,000 CAD / year
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Added 3 hours ago
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Added 3 hours ago
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Lead / Principal Data Engineer - Snowflake & dbt
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…who can go beyond implementing predefined requirements: an engineer who can identify problems, propose sound technical solutions, make informed implementation decisions, and deliver…
Added 3 hours ago
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Senior Software Engineer - Data and AI Platforms
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Vancouver, BC
- Full-time
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Added 4 hours ago
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Montreal, QC
- Full-time
…sector, you are part of a large team and report directly to the Senior Manager. Our team stands out for its commitment to supporting technological transformation and actively contributing…
Added 4 hours ago
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Added 8 hours ago
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Added 8 hours ago
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lululemon

Senior Software Engineer - Data and AI Platforms

Vancouver, BC, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Dec 3, 2026
Experience: 6-10 years of software development experience, building complex systems and driving technical initiatives across teams, or equivalent
Posting language: English
Posted: Nov 3, 2026

Original job description

Requirements

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 team performance. The typical hiring range for this position is from  $132,600 - $174 ,000   annually ; 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
Generous employee discount
Fitness & yoga classes
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.

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More about this job

Responsibilities

Design and build enterprise data systems, AI-enabled platform capabilities, and solutions, including semantic models and retrieval systems that provide reliable context for LLMs. Drive architecture and engineering standards across teams, review complex designs and code, mentor engineers, partner with stakeholders, and lead responses to critical production incidents.

Requirements

Requires a bachelor’s degree in computer science, software engineering, or a related field, or equivalent experience; a master’s degree is beneficial. Candidates should have 6–10 years of software development experience and demonstrated expertise in complex systems, cross-team technical leadership, semantic layers, knowledge representation, and search or RAG architectures.

Skills

Software Engineering
Data Systems
AI Platforms
Semantic Modeling
Knowledge Graphs
Retrieval-Augmented Generation
GraphRAG
Semantic Search
Embeddings
Distributed Systems
API Design
Data Governance
Schema Versioning
System Architecture
Code Review
Incident Response

Benefits

Annual Bonus Program
Extended Health Benefits
Dental Benefits
Mental Health Plans
Paid Time Off
Savings and Retirement Plan Matching
Employee Discount
Fitness and Yoga Classes
Parenthood Top-Up
Development Courses
Mentorship Programs

Visa sponsorship

Not detected in the job text

Keywords

Enterprise Data
Artificial Intelligence
Data Platforms
Data Systems
Semantic Models
Taxonomies
Ontologies
Knowledge Graphs
Large Language Models
Retrieval-Augmented Generation
GraphRAG
Semantic Search
Embeddings
Hybrid Search
Evidence-Based Reasoning
Data Validation
Schema Governance
Versioning
Distributed Systems
APIs
System Architecture
Integration Design
Testing Strategies
Deployment Procedures
AI/ML
Retail
Supply Chain
Customer Data
Product Data
Responsible AI

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