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Director, AI Engineering – Enterprise AI

Offre en anglais
  • Ottawa, ON
  • Sur place
  • Publié 18 août 2026
  • 1 poste

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Type d’emploi
Temps plein
Niveau d’expérience
Chef d’équipe · 10+ ans
Langue de l’offre
anglais
Heures de travail
40 heures par semaine

Résumé du poste

Lead and grow a high-performing AI engineering team while overseeing the design and delivery of enterprise-grade AI applications. Collaborate with cross-functional stakeholders to establish technical standards and drive the strategy for scaling AI capabilities across the organization.

Détails du poste

It's fun to work in a company where people truly BELIEVE in what they're doing! We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! Lumentum Canada was awarded the 2022 National Capital Region’s Top Employers for the 6th consecutive year and the 2022 Career Directory Canada’s Best Employers for Recent Graduates for the 5th consecutive year. Role Summary We are seeking an experienced Director of AI Engineering to build and lead a world-class AI engineering team. This is a critical leadership role responsible for designing and delivering enterprise-grade AI applications that drive business value across Marketing, Finance, Legal, Enterprise Search, and R&D workflows. You will combine deep technical expertise with strong people leadership skills to grow the team, mentor engineers, establish best practices, and scale our AI capabilities across a globally distributed organization. Key Responsibilities Lead and grow an AI engineering team, recruiting top talent and building a high-performing culture focused on technical excellence Design and oversee the delivery of enterprise AI applications across multiple business functions (Marketing, Finance, Legal, Search, R&D) Establish technical standards, architecture patterns, and code review practices that ensure software engineering excellence and maintainability Mentor engineers in modern AI/ML systems design, cloud infrastructure, production deployment, and operational excellence Collaborate with product, data science, and business stakeholders to translate requirements into robust technical solutions Drive technology decisions around AI frameworks, cloud platforms, and infrastructure to optimize for cost, performance, and reliability Build and maintain systems for data pipelines, model serving, monitoring, and continuous improvement of AI applications Lead technical strategy for scaling AI capabilities, including considerations for enterprise security, compliance, and governance Required Qualifications 15+ years of professional software engineering experience with demonstrated progression to senior/leadership roles 3+ years of experience with AI/ML systems (including LLMs, generative AI, RAG architectures, or similar modern AI applications) in production environments 3+ years of technical leadership experience managing and mentoring engineering teams Deep hands-on experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), and modern deployment practices Strong expertise in Python and/or other languages commonly used for AI/ML applications Proven ability to work effectively in globally distributed teams with experience managing across time zones Strong understanding of software engineering best practices: version control, testing, code review, CI/CD, observability Track record of shipping production systems at scale with focus on reliability, performance, and maintainability Excellent communication skills; ability to articulate technical concepts to both technical and non-technical stakeholders Preferred Qualifications Experience in manufacturing, industrial, or enterprise software environments Familiarity with enterprise systems (ERP, CRM, workflow automation) and integration patterns Background in developing retrieval-augmented generation (RAG) systems or knowledge management applications Experience with MLOps, model monitoring, and LLM evaluation frameworks Expertise in establishing and scaling engineering culture, documentation, and knowledge sharing practices Experience with enterprise security, compliance, and data governance requirements Track record of building systems that integrate with modern API ecosystems and third-party AI services

Ce que vous ferez

Lead and grow a high-performing AI engineering team while overseeing the design and delivery of enterprise-grade AI applications. Collaborate with cross-functional stakeholders to establish technical standards and drive the strategy for scaling AI capabilities across the organization.

Exigences

Requires 15+ years of professional software engineering experience with at least 3 years in AI/ML systems and technical leadership. Candidates must possess deep hands-on experience with cloud platforms, containerization, and modern software engineering best practices.

Compétences indiquées

  • Kubernetes · Souhaitée
  • CI/CD · Souhaitée
  • Docker · Souhaitée
  • Apprentissage automatique · Souhaitée
  • Python · Souhaitée

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

  • AI Engineering
  • Machine Learning
  • LLMs
  • Generative AI
  • RAG Architectures
  • Cloud Platforms
  • Python
  • Docker
  • Kubernetes
  • Software Engineering
  • Technical Leadership
  • Data Pipelines
  • Model Serving
  • CI/CD
  • Enterprise Architecture
  • Technical Strategy
  • Concept Drift Detection
  • MLOps (Machine Learning Operations)
  • Generative Artificial Intelligence
  • Enterprise Search
  • Observability
  • Workflow Management
  • Retrieval Augmented Generation
  • Workflow Automation
  • Technology Ecosystems
  • Application Programming Interface (API)
  • Artificial Intelligence
  • Applications Of Artificial Intelligence
  • Amazon Web Services
  • Microsoft Azure
  • Customer Relationship Management
  • Business Valuation
  • Containerization
  • Customer Service
  • Cloud Infrastructure
  • Version Control
  • Code Review
  • Communication
  • Continuous Improvement Process
  • Data Governance
  • Enterprise Resource Planning
  • Enterprise Security
  • Finance
  • Virtual Teams
  • Governance
  • Leadership
  • Marketing
  • Python (Programming Language)
  • Knowledge Management
  • Maintainability

Domaines d’emploi

  • Technology
  • Management & Leadership
  • Software
  • Engineering
  • Data & Analytics
  • Director of AI Engineering
  • Generative Artificial Intelligence Engineer
  • Software Developers
  • Computer and Information Research Scientists

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