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Urban Ridge Supplies

Senior Forward-Deployed AI Engineer

Toronto, ON, Canada

Job type: Full-time
Workplace: Hybrid
Posting language: English
Posted: Sep 24, 2026

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Original job description

Req Id: 431188

At Bell, we do more than build world-class networks, develop innovative services and create original multiplatform media content – we advance how Canadians connect with each other and the world.

If you’re ready to bring game-changing ideas to life and join a community that values, professional growth and employee wellness, we want you on the Bell team.

The Bell Mobility team offers the best and latest mobile devices, wireless services and Internet of Things solutions to consumer and business customers, with the top speeds, coverage and reliability on Canada’s Best National Network. We love to innovate, embrace big challenges, and live for the newest technology

Summary

The Technology Services Applied AI team is a forward-deployed engineering team that embeds across Bell to build, ship, and integrate classical ML, AI agents, and automation into existing enterprise systems.

As a Senior Forward-Deployed AI Engineer, you will own engagements end-to-end: scoping the problem, choosing the right approach across automation, classical ML, and GenAI/agents, and taking solutions from rapid prototype to production-grade agentic workflows (such as multi-agent systems and Model Context Protocol servers) that deliver measurable ROI. Along the way, you will mentor a paired early-career engineer.

Key Responsibilities

Scope the problem with business partners and decide how to solve it: the right approach across rules, automation, classical ML, and GenAI/agents, and where the solution should live across the systems landscape.
Partner with stakeholders to produce solutions with high adoption rates and scalability for ease of growth and reusability across business domains.
Embed into cross-unit squads and lead application builds, owning each engagement end-to-end.
Design, build, and ship production-grade AI agents and automation, integrating with existing enterprise systems and platforms (e.g., Google Cloud, Amazon Bedrock, Salesforce, ServiceNow).
Mentor and pair with an early-career engineer on the engagement.
Depending on experience, own the team's evaluation standards and quality bar.

Critical Qualifications

4-7 years in software engineering, including 2 to 3 years hands-on with GenAI/agents.
Experience designing and deploying AI systems on a major cloud platform (e.g., Google Cloud).
Production experience building and iterating upon agentic applications and the capabilities that power them: agent skills and tools, Model Context Protocol (MCP) servers, and multi-agent workflows, taken from prototype to production.
Experience building data pipelines over structured and unstructured data, using vector databases and retrieval-augmented (RAG) architectures for enterprise AI.
Strong software engineering foundation, including Python, APIs, and integration with production enterprise systems.
A habit of staying current with fast-moving LLM and agent capabilities, patterns, and tooling.

Preferred Qualifications

Experience automating on enterprise platforms (Google Cloud, Amazon Bedrock) and familiarity with our key experience platforms (Google, Salesforce, ServiceNow).
Open-source contributions or published work in the agent or LLM space.
Proven record shipping AI products with measurable financial outcomes (e.g., cost reductions, productivity gains, etc.)
Experience setting up evaluation and observability for agentic systems.
Prior client-facing, consulting, or forward-deployed delivery experience.
Exposure to MLOps/LLMOps for deploying and monitoring in production.

Adequate knowledge of French is required for positions in Quebec.

Additional Information

Position Type: Management

Job Status: Regular - Full Time

Job Location: Canada : Ontario : Toronto

Work Arrangement: Hybrid

Application Deadline: 10/09/2026

For work arrangements that are ‘Hybrid’, successful candidates must be based in Canada and report to a set Bell office for a minimum of 3 days a week. Recognizing the importance of work-life balance, Bell offers flexibility in work hours based on the business needs.

Please apply directly online to be considered for this role. Applications through email will not be accepted.

We know that caring for our team members is at the heart of a healthy, positive and thriving workplace. As part of our team, you’ll enjoy a comprehensive compensation package that includes a competitive salary and a wide range of benefits to support the well-being of you and your family. As soon as you join us, you'll be eligible for medical, dental, vision and mental health benefits that you can tailor to your specific needs. Plus, as a Bell team member, you'll enjoy a 35% discount on our services and access exclusive offers from our partners.

At Bell, we are proud of our focus on fostering an inclusive and accessible workplace where all team members feel valued, respected, supported, and that they belong.

Bell is committed to clarity in our hiring process. All roles posted are opportunities we’re actively recruiting for, unless stated otherwise. We also want to make sure that everyone has an equal opportunity to join our team. We encourage individuals who may require accommodations during the hiring process to let us know. For a confidential inquiry, email your recruiter or recruitment@bell.ca to make arrangements. If you have questions or feedback regarding accessibility at Bell, we invite you to complete the Accessibility feedback form or visit our Accessibility page for other ways to contact us.

Artificial intelligence may be used to assess parts of your application. Please review our privacy policy (see Phenom for details) to learn more about how we collect, use, and disclose your personal information.

Created: Canada, ON, Toronto

Bell, one of Canada's Top 100 Employers.

Job Id: N3j1pAr1V1cwFGKSTwsrXNrEr3aRo1mFsDp1QXKjC7HbFfUiTMcy22MTzSgOrr1wPZeoAk44PFj11+qHbbxdbY6r8kXAl5WZWg==

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More about this job

Responsibilities

The engineer will own end-to-end engagements by scoping problems, designing AI solutions, and integrating them into enterprise systems. They will also lead application builds and mentor early-career engineers within cross-unit squads.

Requirements

Candidates must have 4-7 years of software engineering experience, including 2-3 years of hands-on work with GenAI and agentic systems. Proficiency in Python, cloud platforms, and RAG architectures is required to build and deploy production-grade AI solutions.

Skills

Python
GenAI
AI agents
Machine learning
Cloud platforms
Google Cloud
Amazon Bedrock
Data pipelines
Vector databases
RAG architectures
Model Context Protocol
Automation
Software engineering
APIs
LLMOps
MLOps

Benefits

Medical benefits
Dental benefits
Vision benefits
Mental health benefits
35% discount on services
Competitive salary

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
GenAI
AI Agents
Machine Learning
Python
Google Cloud
Amazon Bedrock
Salesforce
ServiceNow
Model Context Protocol
RAG
Vector Databases
Data Pipelines
Automation
Software Engineering
LLMOps
MLOps
Enterprise Systems
Multi-agent Systems
API
Cloud Computing
Scalability
Prototyping
Production-grade
Mentorship
Stakeholder Management
Consulting
Observability
Evaluation Standards
ROI

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