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About the Role
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 that deliver measurable ROI. You will also mentor a paired early-career engineer.
Responsibilities
- Scope the problem with business partners and decide how to solve it, including the 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.
- Mentor and pair with an early-career engineer on the engagement.
- Own the team's evaluation standards and quality bar, depending on experience.
Requirements
- 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.
- Production experience building and iterating upon agentic applications and their capabilities: 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.
Skills
- GenAI/agents
- AI systems
- Google Cloud
- Amazon Bedrock
- Salesforce
- ServiceNow
- Python
- APIs
- Vector databases
- Retrieval-augmented (RAG) architectures
- Model Context Protocol (MCP) servers
- Multi-agent workflows
- LLM
Location
- Toronto, Ontario, Canada
Work Type
- Hybrid
- Regular - Full Time
Experience Level
- Senior
- Management
Benefits
- Competitive salary
- Medical, dental, vision and mental health benefits
- 35% discount on services
- Exclusive offers from partners
About the Company
- Bell is one of Canada's Top 100 Employers.
- 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.
- 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.
Equal Opportunity
- Bell is committed to fostering an inclusive and accessible workplace where all team members feel valued, respected, supported, and that they belong.
- 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.