Senior Forward-Deployed AI Engineer

Req

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

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.

• 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, Service Now).
• Mentor and pair with an early-career engineer on the engagement.
• Depending on experience, own the team's evaluation standards and quality bar.

• 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.

• Experience automating on enterprise platforms (Google Cloud, Amazon Bedrock) and familiarity with our key experience platforms (Google, Salesforce, Service Now).
• 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.

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Adequate knowledge of French is required for positions in Quebec.

• Position Type:
  Management
• Job Status:
  Regular - Full Time
• Job Location:
  
  Canada :
  Ontario :
  Toronto
• Work Arrangement:
  Hybrid
• Final date to receive applications: 10/09/2026

For…