Senior Forward Deployed AI Engineer

14 days ago

Montréal, CanadaSenior

Responsibilities

Embed into transformation squads and lead agentic software development engagements end-to-end.
Scope business problems and determine whether automation, rules, classical machine learning, GenAI, or agents are the appropriate solution.
Design, build, integrate, and ship production-grade AI agents and automation across enterprise systems and platforms.
Develop multi-agent workflows, Model Context Protocol servers, data pipelines, vector-database solutions, and retrieval-augmented architectures.
Recognize when bespoke modeling is needed and route those use cases to the central data science team.
Mentor and pair with an early-career engineer.
Depending on experience, own evaluation standards and the quality bar for agentic systems.
Deliver solutions with measurable financial or productivity outcomes.

Production experience building agentic applications, agent skills and tools, Model Context Protocol servers, and multi-agent workflows from prototype through production.
Experience designing and deploying AI systems on a major cloud platform such as Google Cloud.
Experience building data pipelines over structured and unstructured data using vector databases and retrieval-augmented architectures.
Strong software engineering foundation, including Python, APIs, and integration with production enterprise systems.
Ability to stay current with rapidly evolving LLM and agent capabilities, patterns, and tooling.
5 to 10 years of software engineering experience, including 2 to 3 years of hands-on GenAI or agent experience.
Experience automating on enterprise platforms such as Google Cloud and Amazon Bedrock, with familiarity with Google, Salesforce, and ServiceNow.
Professional experience at a hyperscaler or startup is considered an asset.
Open-source contributions or published work in the agent or LLM space are preferred.
Proven experience shipping AI products with measurable financial outcomes is preferred.
Experience establishing evaluation and observability for agentic systems is preferred.
Exposure to MLOps or LLMOps for production deployment and monitoring is preferred.
Prior client-facing, consulting, or forward-deployed delivery experience is preferred.
Adequate knowledge of French is required for positions in Quebec.

Hybrid work arrangement in Canada, with reporting to a Bell office at least three days per week.
Regular full-time position with flexible work hours based on business needs.
Medical, dental, vision, and mental health benefits available upon joining.
35% discount on Bell services and access to exclusive partner offers.
Inclusive and accessible workplace with accommodations available during the hiring process.

Google CloudPython