Senior Software Engineer - Ai Tech And It : Drivewyze · Remote (Alberta) Open Until Filled

Fleetworthy offers the only complete technology suite for fleet readiness, uniting safety and compliance, toll management, and weigh station bypass solutions. We help fleets streamline operations, control costs, andoperatewith confidence.
Trusted by 75% of the top fleets in North America,Fleetworthyoffers the most adopted toll management solution and largest weigh station bypass network. Going beyond regulatory requirements, oursafety andcompliance capabilities strengthen safety programs and enable proactive audit readiness. We support millions of vehicles and drivers and are recognized across the industry for innovation and leadership.
Fleetworthy is shaping the future of fleet readiness with AI-enabled, connected fleet technology that keeps drivers safe, fleets compliant, and operations running at peak efficiency. Learn more at fleetworthy.Com.
About the role:We're hiring a Senior Software Engineer for the AI Platform team. The team builds AI agents and products across Fleetworthy's fleet readiness suite, the shared platform they run on, and the tooling that helps every engineering team build with agents. Above all, we need someone who ships working software to production and keeps it running.
The work spans four areas:
AI agents and products
for customers and internal teams, across safety and compliance, toll management and weigh station bypass
Enterprise context layer
that gives agents permission-aware access to company knowledge and data
Agentic engineering
tooling and practices used across all engineering teams
Automated workflows
for problems that don't need an agent
What you ship affects fleet safety, compliance and operations directly. This is a senior role on a small team: you'll own systems long term and help set how engineering builds with agents.
Responsibilities:
Ship working software to production frequently, in small increments, and lead projects end to end from spec to launch
Build and deploy AI agents and AI features for customers and internal teams
Build and extend the enterprise context layer: connectors, retrieval, permission enforcement and MCP access
Build shared tooling and practices that help other teams build with agents
Choose between an agent and a deterministic workflow, and build either
Provision and run the infrastructure behind what you build: environments, pipelines and deployments
Turn loose problems from product, support and engineering into clear requirements
Own what you ship once it's live: monitoring, evals, cost and failure handling Mentor engineers on the team and across engineering
How we work:Our engineers use coding agents as their main way of building software. Most of your time goes to defining work, checking what agents produce and making the calls that matter. That means breaking work into pieces an agent can finish and you can verify, running agents in parallel, and relying on tests, CI and agent review so speed doesn't cost quality.
Requirements:
Senior engineer with a track record of shipping software to production frequently and owning it after release
Experience shipping AI agents or AI features to production that users rely on today Proficiency in Agentic SDLC, with coding agents as the primary way of building software
Advanced skills with Python and/or TypeScript
Hands-on experience with LLM APIs, MCP and agent frameworks, including when not to use one
Experience with retrieval systems (search, RAG) and permission-aware data access Experience using evals and data to decide when an agent is ready to ship and whether it's working
DevOps experience: Docker, Kubernetes or managed container platforms, infrastructure as code (Terraform or similar) and building CI/CD pipelines
Experience running production services: observability (Datadog or similar), alerting,
secrets and identity management, and incident response
Proficient in SQL and PostgreSQL
Strong live communication skills, ability to work independently, and candor about what you don't know
Preferred, but not required:
Background in fleet operations, transportation or logistics
Databricks, including Unity Catalog or Genie
Enterprise search connectors (Confluence, SharePoint, Jira, Slack) and vector databases
Identity and access control for services and agents
Workflow orchestration or automation platforms
Azure (App Service, AKS, Azure DevOps) or AWS
Fleetworthy is committed to fostering a diverse and inclusive culture that is respectful and welcoming of individual differences. We are proud to be an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, nationality, national or ethnic origin, civil status, age, citizenship status, sexual orientation, disability, genetic information, familial status, marital or registered civil partnership status, pregnancy or maternity status, gender identity, gender reassignment, military or veteran status, or any other protected characteristic in accordance with applicable laws and regulations.
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