Senior Software Engineer - AI

CanadaRemoteFull-time

Software EngineerSoftware Engineering

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Quick Summary

Overview

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer – AI based in Canada.

Technical Tools

Software EngineerSoftware Engineering

The Senior Software Engineer will join a small AI Platform team responsible for building production-ready AI agents, intelligent products, and shared infrastructure across a connected fleet technology ecosystem. You will develop solutions supporting fleet safety, regulatory compliance, toll management, and weigh station bypass operations. The role also involves creating enterprise context layers that provide secure, permission-aware access to organizational knowledge and data. You will help establish agentic engineering practices and tools that enable other engineering teams to build more effectively with AI. This is a hands-on senior position with end-to-end ownership, from architecture and development through deployment, monitoring, and continuous improvement. You will work in an AI-first engineering environment where coding agents are central to software delivery.

Lead projects end to end, translating specifications and loosely defined business problems into clear requirements, implementation plans, and production launches.
Consistently deliver working software to production through frequent, incremental releases.
Design, build, and deploy AI agents and AI-powered features for both customer-facing products and internal teams.
Develop and extend the enterprise context layer, including data connectors, retrieval systems, permission enforcement, and Model Context Protocol (MCP) access.
Build shared tooling, frameworks, and engineering practices that help teams across the organization develop and deploy AI agents effectively.
Evaluate whether a problem is best addressed through an AI agent or a deterministic automated workflow, and implement the most appropriate solution.
Provision and manage the infrastructure supporting applications, including environments, deployment pipelines, and production releases.
Take long-term ownership of deployed systems, including monitoring, evaluation, cost management, reliability, and failure handling.
Use tests, continuous integration, and agent-based review practices to maintain software quality while working with coding agents.
Break down development tasks into manageable work that coding agents can execute and engineers can verify, coordinating multiple agents in parallel where appropriate.
Mentor engineers within the AI Platform team and across the wider engineering organization.
Collaborate with product, support, and engineering stakeholders to identify opportunities and deliver practical technical solutions.

Requirements

~2 min read

Demonstrated experience as a senior software engineer, with a strong track record of frequently shipping production software and maintaining ownership after release.
Proven experience delivering AI agents or AI-powered features to production that are actively used and relied upon by users.
Strong proficiency in Python and/or TypeScript.
Advanced experience with agentic software development lifecycle (Agentic SDLC), using coding agents as a primary method of building software.
Hands-on experience with large language model (LLM) APIs, MCP, and agent frameworks, including sound judgment about when an agent-based approach is appropriate and when it is not.
Experience designing and implementing retrieval systems, including search, Retrieval-Augmented Generation (RAG), and permission-aware data access.
Familiarity with evaluation frameworks and data-driven methods for determining whether AI agents are ready for production and performing effectively.
DevOps and infrastructure experience, including Docker, Kubernetes or managed container platforms, infrastructure as code (Terraform or equivalent), and CI/CD pipeline development.
Experience operating production services, including observability tools such as Datadog or similar platforms, alerting, secrets and identity management, and incident response.
Strong SQL skills and practical experience with PostgreSQL.
Excellent communication skills, including the ability to communicate effectively in live discussions, work independently, and be transparent about technical limitations or knowledge gaps.
Strong problem-solving skills, sound technical judgment, and the ability to take ownership in a fast-moving engineering environment.

Preferred qualifications:

Experience or knowledge of fleet operations, transportation, or logistics.
Experience with Databricks, including Unity Catalog or Genie.
Familiarity with enterprise search integrations and connectors such as Confluence, SharePoint, Jira, and Slack.
Experience with vector databases and retrieval infrastructure.
Knowledge of identity and access control for services and AI agents.
Experience with workflow orchestration or automation platforms.
Familiarity with cloud environments such as Azure (App Service, AKS, Azure DevOps) or AWS.