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Salary
$103k – $221k per year (Estimated)
Location
In office (Ottawa)
Seniority
Architect · 15+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Lumentum is a technology company headquartered in San Jose, California, and was established as an independent entity in 2015 following a spin-off from JDS Uniphase. The company designs and manufactures optical and photonic products, including lasers for industrial manufacturing, optical transceivers for data centers, and 3D sensing components for consumer electronics. It operates a global network of manufacturing and research facilities, serving customers in the telecommunications, cloud networking, and industrial markets worldwide.

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
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