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
