Senior Forward-Deployed AI Engineer 1

Role summary

Key responsibilities

• Scope business problems and choose among rules, automation, classical machine learning, and GenAI or agent approaches.
• Partner with stakeholders to create scalable, reusable solutions with strong adoption.
• Lead application builds in cross-unit squads and own engagements end to end.
• Build and ship production AI agents and automation integrated with enterprise platforms such as Google Cloud, Amazon Bedrock, Salesforce, and ServiceNow.
• Mentor an early-career engineer and, depending on experience, own evaluation standards and quality.

Critical qualifications

• Four to seven years in software engineering, including two to three years hands-on with GenAI or agents.
• Experience automating on enterprise platforms such as Google Cloud and Amazon Bedrock and familiarity with Google, Salesforce, and ServiceNow platforms.
• Open-source contributions or published work in the agent or LLM space.
• Record of shipping AI products with measurable financial outcomes.
• Experience establishing evaluation and observability for agentic systems.
• Prior client-facing, consulting, or forward-deployed delivery experience.
• Exposure to production MLOps or LLMOps is preferred.

Preferred qualifications

• AI-system design and deployment on a major cloud platform is preferred.
• Production agentic applications, MCP servers, multi-agent workflows, and prototype-to-production delivery are preferred.
• Structured and unstructured data pipelines, vector databases, and RAG architectures are preferred.
• Python, APIs, and production enterprise-system integration are preferred.

Work arrangement

• The position is hybrid and based in Toronto, Ontario.
• Hybrid employees must be based in Canada and report to a Bell office at least three days per week.
• Work-hour flexibility is available based on business needs.

Position details