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About the Role
The Technology Services Applied AI team is a forward-deployed engineering team that builds, ships, and integrates 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 problems, 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 an early-career engineer.
Responsibilities
- Scope the problem with business partners and decide how to solve it, including the approach (rules, automation, classical ML, GenAI/agents) and solution placement within 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.
- 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 (e.g., Google Cloud).
- Production experience building and iterating upon agentic applications and their capabilities: agent skills and tools, Model Context Protocol (MCP) servers, and multi-agent workflows, 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.
- Adequate knowledge of French is required for positions in Quebec.
Skills
- GenAI/agents
- AI systems
- Google Cloud
- Amazon Bedrock
- Salesforce
- ServiceNow
- Agentic applications
- Model Context Protocol (MCP) servers
- Multi-agent workflows
- Data pipelines
- Vector databases
- Retrieval-augmented (RAG) architectures
- Python
- APIs
- Enterprise systems integration
- LLM capabilities
- Agent capabilities
- Agent patterns
- Agent tooling
- MLOps/LLMOps
Location
- Canada
- Ontario
- Toronto
Work Type
- Hybrid
- Management
- Regular - Full Time
Experience Level
- Senior
Benefits
- Comprehensive compensation package
- Competitive salary
- Medical benefits
- Dental benefits
- Vision benefits
- Mental health benefits
- 35% discount on services
- Exclusive offers from partners
About the Company
- Bell is one of Canada's Top 100 Employers.
- Bell advances how Canadians connect with each other and the world.
- Bell Mobility offers the best and latest mobile devices, wireless services and Internet of Things solutions with top speeds, coverage and reliability on Canada’s Best National Network.
Equal Opportunity
- Bell is 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.
- 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.