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: