AI Engineer
Our team and what we will accomplish together
TELUS' Door-to-Door (D2D) channel is one of our largest residential sales channels, made up of field sales representatives who engage customers directly in their communities to sell and support TELUS products and services. Our team, Data Analytics & Innovation for D2D, provides the data, tools, technology, and insights that enable this channel to operate effectively. The D2D AI Innovation Hub is a newly established team within this broader group, building AI-driven tools and automation across two pillars: D2D Channel AI Innovation and Partner Ecosystem & Comp AI — spanning rep enablement and coaching tools, territory and CRM optimization, compensation modeling, and quality and audit automation.
We are looking for an AI Engineer to design, build, and deploy agentic AI applications and automation workflows that solve real problems for our field sales channel. This role is ideal for someone who is equally comfortable prototyping quickly and shipping production-grade solutions, who can translate ambiguous business problems into working AI systems, and who wants to help stand up a brand-new AI capability from the ground up.
What you will do
- Design, build, and deploy agentic AI applications and automation workflows using tools such as n8n, KNIME, and GCP/Vertex AI.
- Develop and productionize AI solutions across the D2D AI Innovation Hub's focus areas, including rep enablement, territory scoring, CRM automation, and compensation modeling.
- Build and maintain integrations between AI systems and enterprise data sources, including BigQuery and MCP (Model Context Protocol) servers.
- Turn ambiguous business requirements into working prototypes and iterate quickly with SMEs and stakeholders.
- Apply large language models and NLP techniques to unstructured field-sales data to surface insights, automate manual work, and improve rep and channel performance.
- Collaborate with data analytics and engineering teams to ensure AI solutions are reliable, scalable, and well integrated with existing data pipelines.
- Support feasibility assessments and MVP scoping for new AI use cases, balancing ambition with delivery timelines.
- Document architecture, workflows, and model behavior clearly for both technical and non-technical audiences.
What you bring
- 3+ years of experience as an AI/ML Engineer, Data Scientist building and deploying AI-powered applications.
- Hands-on experience building agentic AI workflows and automations (e.g., n8n, LangChain, or similar orchestration frameworks).
- Working knowledge of cloud AI platforms such as GCP (Vertex AI, BigQuery) and experience integrating LLM APIs into production systems.
- Solid programming skills in Python and/or JavaScript, with experience building and consuming APIs.
- Practical understanding of NLP, machine learning fundamentals, and data science workflows.
- Experience with low-code/no-code data tools such as KNIME is an asset.
- Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders.
- Comfort operating in a fast-paced, ambiguous, early-stage environment and iterating on rapidly evolving priorities.
Great-to-haves
- Experience supporting sales, field operations, or revenue-focused teams.
- Telecom or large enterprise experience.
Pay: $120,000.00-$130,000.00 per year
Benefits:
- Extended health care
- Paid time off
- Work from home
Work Location: Hybrid remote in Toronto, ON (York District)