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À propos de ce poste Engineering Manager, Agentic AI & Machine Learning chez Loblaw

Loblaw · Sur site · 500 Lake Shore Blvd W, Toronto, ON

Come make your difference in communities across Canada, where authenticity, trust and making connections is valued – as we shape the future of Canadian retail, together. Our unique position as one of the country's largest employers, coupled with our commitment to positively impact the lives of all Canadians, provides our colleagues a range of opportunities and experiences to help Canadians Live Life Well®.

At Loblaw Companies Limited, we succeed through collaboration and commitment and set a high bar for ourselves and those around us. Whether you are just starting your career, re-entering the workforce, or looking for a new job, this is where you belong. 

Our teams are applying Agentic AI, Generative AI, and Machine Learning to solve complex problems across retail media, advertising, and digital commerce. From intelligent campaign creation and conversational analytics to forecasting, recommendations, and optimization, we're building AI systems that deliver meaningful business impact at scale.


We're looking for an Engineering Manager, Agentic AI & Machine Learning to lead a talented team of engineers developing and operating these capabilities.


This is an opportunity for a technically strong, hands-on engineering leader who enjoys working at the intersection of emerging AI technologies, scalable software systems, and real-world business problems. You'll help shape our AI engineering direction, grow a high-performing team, and take ownership of delivering reliable, production-grade solutions.


What You'll Do:


  • Lead and grow a high-performing engineering team: Manage, mentor, and develop talented AI/ML engineers, fostering technical excellence, ownership, collaboration, and continuous learning.
  • Drive Agentic AI innovation: Lead the architecture and development of AI-powered applications incorporating LLMs, agent orchestration, tool calling, retrieval, and intelligent workflows.
  • Build impactful Machine Learning solutions: Guide the development and productionization of ML models supporting forecasting, recommendations, relevance, targeting, and optimization.
  • Own end-to-end engineering delivery: Translate product strategy and business requirements into scalable technical solutions, taking ownership from architecture and development through deployment and ongoing operations.
  • Establish strong AI engineering practices: Champion robust evaluation frameworks, automated testing, observability, and continuous improvement of model quality, response accuracy, latency, reliability, and cost efficiency.
  • Provide technical leadership: Guide architectural decisions, design reviews, and engineering trade-offs across AI systems, distributed services, data pipelines, and cloud infrastructure. Remain close enough to the technology to help teams navigate complex engineering challenges.
  • Collaborate across functions: Partner closely with Product Management, Data Engineering, Software Engineering, and business stakeholders to define priorities, manage dependencies, and deliver measurable outcomes.
  • Build for production at scale: Promote sound engineering practices across CI/CD, MLOps, LLMOps, security, responsible AI, incident management, and operational readiness.
  • Shape the future of our AI capabilities: Evaluate emerging technologies, challenge existing approaches, and identify opportunities to build reusable engineering foundations that accelerate future product development.


Does This Sound Like You?


  • 7+ years of professional experience in Software Engineering, Machine Learning Engineering, or related technical disciplines, including substantial experience building AI/ML-powered systems.
  • 2+ years of experience leading and mentoring technical teams, with demonstrated ability to develop engineers, manage delivery, and create a culture of accountability.
  • Proven experience designing, developing, and deploying production-grade AI/ML solutions, with a strong understanding of scalability, reliability, and operational requirements.
  • Strong understanding of modern AI technologies, including LLMs, Generative AI, agentic workflows, retrieval-augmented generation (RAG), and techniques for evaluating AI system quality.
  • Solid foundation in applied Machine Learning, including model development, evaluation, experimentation, and production deployment.
  • Strong software engineering fundamentals, with proficiency in Python and experience building APIs, distributed systems, and cloud-native applications.
  • Familiarity with modern AI/ML infrastructure, including model serving, orchestration, automated deployment, monitoring, and observability.
  • Demonstrated ability to lead complex technical initiatives, balance short-term delivery with long-term architectural decisions, and navigate ambiguity.
  • Excellent communication and stakeholder management skills, with the ability to explain complex technical concepts, influence decisions, and collaborate across engineering and product teams.


Nice to Have:


  • Experience building production agentic systems using frameworks such as LangGraph, LangChain, CrewAI, or similar technologies.
  • Familiarity with Model Context Protocol (MCP), agent evaluation, human-in-the-loop workflows, and AI observability tools such as Langfuse.
  • Experience with Google Cloud Platform, Vertex AI, Gemini, or comparable cloud-based AI platforms.
  • Experience with recommendation systems, search and ranking, forecasting, experimentation, or optimization algorithms.
  • Exposure to Retail Media, AdTech, eCommerce, or large-scale customer-facing digital products.
  • Experience establishing engineering practices for teams building both traditional ML models and Generative AI applications.



Our commitment to Sustainability and Social Impact is an essential part of the way we do business, and we focus our attention on areas where we can have the greatest impact. Our approach to sustainability and social impact is based on three pillars – Environment, Sourcing and Community – and we are constantly looking for ways to demonstrate leadership in these important areas. Our CORE Values – Care, Ownership, Respect and Excellence – guide all our decision-making and come to life through our Blue Culture. We offer our colleagues progressive careers, comprehensive training, flexibility, and other competitive benefits – these are some of the many reasons why we are one of Canada’s Top Employers, Canada’s Best Diversity Employers, Canada’s Greenest Employers & Canada’s Top Employers for Young People.

If you are unsure whether your experience matches every requirement above, we encourage you to apply anyway. We are looking for varied perspectives which include diverse experiences that we can add to our team.

We have a long-standing focus on diversity, equity and inclusion because we know it will make our company a better place to work and shop. We are committed to creating accessible environments for our colleagues, candidates and customers. Requests for accommodation due to a disability (which may be visible or invisible, temporary or permanent) can be made at any stage of application and employment. We encourage candidates to make their accommodation needs known so that we can provide equitable opportunities.  
 
Please Note:
Candidates who are 18 years or older are required to complete a criminal background check. Details will be provided through the application process.

Hiring Range / Échelle salariale à l’embauche :

$170,000.00 - $220,000.00 / 170.000,00$ - 220.000,00$ (per year / par an)

A candidate’s experience and knowledge as well as the geographical region in which the position is located may be factored into the pay a candidate receives for this position. This posting is for an existing vacancy. The Company uses artificial intelligence for the purpose of screening, assessing and/or selecting applicants for this position. / L’expérience et les connaissances d’un candidat ainsi que la région géographique dans laquelle le poste est situé peuvent être prises en compte dans la rémunération qu’un candidat reçoit pour ce poste. Cette offre d’emploi concerne un poste vacant existant. L’entreprise utilise l’intelligence artificielle dans le but de filtrer, d’évaluer et/ou de sélectionner les candidats à ce poste.

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Comment se compare ce salaire pour Engineering Manager

Ce poste paie $195,000/yr — dans la fourchette habituelle pour les postes Engineering Manager.

$98,750 la médiane $169,800 $257,500

Fourchette typique $132,500–$211,500/yr, à partir de 3,611 annonces Engineering Manager comparables sur JobsRadar (rémunération annualisée en USD). Voir les aperçus de salaire pour Engineering Manager →

À propos de Loblaw

Please be advised that recruitment fraud has affected a number of Canadian companies. In such schemes, individuals posing as legitimate recruiters may request personal information and payment from those seeking employment. Loblaw Companies Limited, its subsidiaries, and recruiting agencies will never ask for payment at any stage in the recruitment process. To avoid falling victim to recruitment fraud: Do not to respond to unsolicited offers from people you are unfamiliar with Do not disclose personal or financial details via text messages Check any documents for poor grammar and spelling as this is often a warning sign of fraud Beware of employers or agents using webmail email addresses such

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