Director of Engineering

About the job

The Mission:

As a Director of Engineering at Telus Digital, you will build and lead a high-performing team that delivers customer-loved products with exceptional quality, speed, and reliability. You will define the technical vision and provide enterprise-level architectural guidance to ensure our platforms are scalable, secure, and seamlessly integrated with our business strategy.

What you will do

Own Delivery & Reliability:

Drive the end-to-end delivery of AI-powered products and features. Drive quarterly planning and execution, ensure commitments are met on time, and uphold high availability, low latency, and deliver measurable business value. Define Enterprise Architecture:

Partner with cross-functional leadership to define the enterprise-wide technical strategy for Telus Digital's AI initiatives. Establish architectural standards, best practices, and governance frameworks to ensure consistency and quality across the organization. Lead future Leaders:

Hire, coach, and develop a high-performing team of Engineers,Managers, and specialised technical talent. Foster a culture of technical excellence, accountability, and continuous learning to meet the evolving needs of the business. Champion Engineering Excellence:

Drive a culture of quality, velocity, and continuous improvement. Set and maintain high standards for code health, test coverage, and developer experience to ensure sustainable development. Shape Strategy with Product:

Partner with Product , Research and other critical stakeholder teams to translate strategic business goals into a focused roadmap. Make data-driven decisions Raise the Technical Bar:

Guide architectural choices, unblock critical designs, and sponsor platform investments that reduce cycle time and improve the overall developer experience. Operational Excellence:

Establish and enforce strong practices for on-call support, incident response, change management, and post-incident learning. Ensure that reliability and security are a shared responsibility for all team members. Scale the Organization:

Design the team topology for a growing AI division. Define clear interfaces between research, data, engineering and all critical teams to ensure a fluid and efficient workflow. Budget and Vendor Stewardship:

Own headcount plans and operating budgets. Evaluate buy vs. build decisions and manage relationships with strategic partners Strategic Agility:

Be agile within an enterprise organization, and be ready to step up and evolve strategically to meet any evolving needs to grow the organization.

Qualifications: 12+ years in software engineering with 4+ years leading engineers and managers in multi-team organizations. Demonstrated experience in building, deploying, and managing complex, customer-facing systems preferably powered by Ml/AI at scale. Strong architectural judgment across a broad range of systems, data stores, API and modern full stack technologies, with a proven ability to design and govern large-scale systems. You have experience defining and socializing architectural standards. Strong technical background with the capability of being hands-on if required and earning the respect and ability to mentor top individual technical talent. Excellent people leadership skills, with a proven ability to set crisp goals, coach for performance, and build healthy, diverse teams. A data-driven approach to planning, trade-offs, and process improvement. Exceptional communication and interpersonal skills, with the ability to simplify complex concepts, negotiate effectively, and make clear decisions with executives and cross-functional partners. Fluency in delivery operations, including experience with on-call, incidents, and change management. Proven record of leading, mentoring, and scaling diverse teams of engineers from diverse top tier colleges and fortune top engineering companies Fluency with Data Engineering, Data Ops and Cloud practices, including data pipelines, feature stores, model training, versioning, and monitoring.

Nice to have Direct experience with technologies like TensorFlow, PyTorch, Kubernetes, Kubeflow, or MLOps platforms. Experience with responsible AI practices and frameworks for fairness, privacy, and explainability. Hands-on background with one or more of our technologies: Java, Go, Python, Node, React, TypeScript, Kubernetes, Postgres, Kafka, Redis, BigQuery or Snowflake, Terraform. Practical exposure to ML or LLM-powered features, evaluation frameworks, and responsible AI practices.

About us: https://drive.google.com/file/d/1Cq1cmk-ND-MDZVZcBdpIyhd5PfQOdQK-/view?usp=drive_link