Position SummaryMost companies can prototype with AI. Far fewer can deploy what they built, keep it running, and trust the data underneath it. Closing that gap is this job.
The AI Platform Engineer builds and runs the ground the AI Solutions team stands on: the environments where internal applications and agents deploy, the data pipelines that feed them, the CI/CD that moves code from pull request to production safely, and the rules for what an AI coding agent may and may not do on its own. You are the first engineer on the team, and the standards you set are the ones every later build follows.
Position Responsibilities- Design and operate the environments where internally built applications, dashboards, and AI agents run: hosting, networking, identity, secrets, and monitoring.
- Build and maintain the data pipelines between Microsoft Fabric and our systems of record (ERP, CRM, telematics, and others), including refresh cadence, lineage, and named ownership.
- Own CI/CD for internally built software: repositories, review gates, automated tests, environments, and promotion to production.
- Define and enforce the guardrails for AI-assisted development: what an agent may generate, what a person must review, what may reach production, and how we know it worked.
- Implement access control: single sign-on, role-based access, secrets management, read-only service accounts, and the audit trail behind them.
- Run the toolchain the team builds with, including coding agents such as Claude Code, evaluation harnesses, and shared libraries.
- Turn one-off deployments into repeatable patterns: templates, infrastructure as code, and a paved road that a full-stack engineer or analyst can follow without you in the room.
- Monitor cost, performance, and reliability of deployed workloads, and report on all three.
- Partner with IT on network, identity, and endpoint decisions rather than working around them.
Position Qualifications
- Bachelor's degree in computer science, information systems, or equivalent working experience.
- Minimum 5+ years in platform, DevOps, data, or infrastructure engineering.
- Hands-on Azure experience across identity, networking, and application hosting.
- Production CI/CD experience with GitHub Actions, Azure DevOps, or equivalent.
- Strong SQL, plus Python or PowerShell for automation.
- Experience building and operating data pipelines that other people depend on.
- Practical experience running AI coding agents inside a controlled workflow, with a point of view on what they may and may not do unsupervised.
- Able to write a standard clearly enough that another engineer follows it without a meeting.
- Wants to grow as an AI-assisted engineer: you already use these tools to do your own work faster and you want to get better at it.
Ideal Candidates Will Also Have
- Microsoft Fabric, Synapse, or Databricks experience in production.
- Infrastructure as code with Terraform or Bicep.
- Containers in production: Docker with Azure Container Apps, App Service, or Kubernetes.
- Experience integrating with an ERP, MES, or telematics platform.
- Background as the first or only platform engineer on a small team.
- Manufacturing or field service exposure.
