Senior Manager, Solutions Architecture - Data & AI

Who we are

Welcome to TELUS Digital, where innovation makes a global impact. As an award-winning digital product consultancy and the digital division of TELUS, one of Canada's largest telecommunications providers, we design and deliver transformative customer experiences through cutting-edge technology, agile thinking and a people-first culture.

With a global team present in North America, South America, Central America, Europe, Africa and Asia-Pacific, we offer end-to-end expertise across eight core service areas: Digital Product Consulting, Digital Marketing Services, Data and AI, Strategy Consulting, Business Operations Modernisation, Enterprise Applications, Cloud Engineering and QA and Testing Engineering.

From mobile apps and websites to voice interfaces, chatbots, AI, customer service and in-store solutions, TELUS Digital enables seamless, reliable and digitally powered experiences that reach customers wherever they are, all supported by the secure infrastructure and scale of our multi-billion-dollar parent company.

Location and flexibility

This role may be performed in Hybrid mode (Work From Near) in one of the following offices: Boston, MA, Columbus, OH, Charlottesville, VA or Durham, NC, OR in full remote mode (Work From Anywhere) with planned travel to clients and TELUS Digital Solutions offices.

The opportunity

As a Senior Manager, Solutions Architecture specialising in Data and AI, you will play a key role in bridging pre-sales strategy and project delivery. Drawing on your in-depth knowledge of data ecosystems, machine learning and AI technologies, you will help design, architect and launch high-impact solutions aligned with the objectives of clients and executive partners. Whether you are leading architectural discovery for new Data and AI initiatives or guiding ongoing projects, you will ensure that solutions are both technically sound and aligned with business and operational goals.

You will work with prospective clients to explore how our capabilities can address their unique data and AI challenges, lead architecture efforts for new engagements and work closely with delivery teams to bring customers' visions to life. You will also provide essential estimates regarding team composition, project scope and resource planning, ensuring that Data and AI projects are realistically defined and staffed for success.

Between engagements, you will bring your expertise across teams as a flexible problem solver, while deepening your knowledge in areas such as cloud data platforms (e.g., Databricks, Snowflake, Azure, AWS, GCP) or advanced AI/ML methodologies.

Responsibilities

Pre-sales: Lead scoping, technical design and work planning during the pre-sales process, presenting our Data and AI capabilities to prospective clients.

Delivery: Take a leading role in technical architecture and discovery projects, using consulting methods to refine the architecture of data products and the technical architecture of client projects. This includes designing scalable data pipelines, machine learning model architectures and MLOps frameworks.

Subject matter expertise: Own a "technology vertical" within Data and AI, covering solution design, platform selection (e.g., Databricks, Snowflake, AWS Bedrock), implementation support and thought leadership. This may include areas such as large-scale data warehousing, real-time analytics, machine learning operations (MLOps) or agentic AI systems.

Roaming catalyst: Strengthen existing project teams with account-level architectural guidance or specific subject matter expertise in data engineering, machine learning or artificial intelligence.

Qualifications

• Multi-platform familiarity, with expertise in one or more of the following areas:

  • Cloud data platforms: In-depth experience with Databricks, Snowflake or other major cloud data warehouse/lakehouse solutions

  • Cloud AI/ML services: Mastery of cloud-native AI/ML platforms (e.g., AWS Bedrock / SageMaker, Azure ML, Google AI Platform/Vertex AI)

  • Cloud backend platforms: Strong experience with the leading cloud providers (AWS, Azure, GCP) for deploying and managing data and AI solutions

  • Data and AI industry expertise: Specialised knowledge of the data ecosystem, including data ingestion, ETL/ELT processes, data warehousing, data lakes and real-time analytics

  • Machine learning and AI proficiency: Candidates must be familiar with current trends in machine learning (supervised, unsupervised, deep learning), MLOps and advanced AI concepts such as agentic AI or large language models (LLMs)

• Technical skills:

  • In-depth understanding of MLOps principles and continuous integration/continuous delivery (CI/CD) tools for machine learning models

  • Familiarity with containerisation (Docker) and orchestration (Kubernetes) for scalable deployments

  • Experience in software estimation, work planning and developing project plans within time and cost constraints

  • Attention to detail and ability to navigate ambiguity

• Experience delivering software or data solutions in an agency or client service environment

• Ability to clearly break down complex Data and AI concepts for both technical and non-technical audiences, including executive-level stakeholders

• Experience in commercial conversations involving budgets and fees related to Data and AI initiatives

• Passion for applying modern processes that transform client organisations (e.g., continuous delivery, rapid iteration and agile-inspired methodologies for data and ML)

• Excellent verbal and written communication skills

• Ability to use repeatable frameworks and best practices to integrate new data technologies or AI concepts

• Interest in the client's business as a whole, beyond a single data project or AI initiative, and a desire to grow an account to serve a client holistically

• As comfortable in pre-sales environments as in post-sales

Employment equity employer

At TELUS Digital, we are proud to be an employment equity employer and are committed to creating a diverse and inclusive workplace. All aspects of employment, including the decision to hire and promote, are based on candidates' qualifications, merit, skills and performance, without regard to any diversity-related characteristic.

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