Senior Software Engineer - AI

Fleetworthy; Edmonton; On-site; CAD 140,000 - 190,000; Full time

Job summary

Fleetworthy is seeking a Senior Software Engineer for the AI Platform team. You will build AI agents and products across the fleet readiness suite, the shared platform, and tooling that enables engineering teams to work with agents. You will own long‑term systems and guide how engineering teams ship with agents.

The role spans AI agents, enterprise context layer, agentic tooling, and automated workflows. You will ship incrementally, mentor peers, and ensure reliability and scalability of

Qualifications

• 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.

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

Skills

Shipping software production

Independent work

Communication

Tools

Python

TypeScript

LLM APIs

MCP

Agent frameworks

Docker

Kubernetes

Terraform

CI/CD

Datadog

SQL

PostgreSQL

Job description

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, an d opera te with confidence. Trusted by 75% of the top fleets in North America, Fleetworthy offers the most adopted toll management solution and largest weigh station bypass network. Going beyond regulatory requirements, our safety and compliance 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

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.