AI Platform Engineering

Airoom has spent 65 years becoming the most trusted design-build firm in Chicagoland - 20,000 projects, two showrooms, and a reputation built on craftsmanship and process. That process is now getting an entirely new layer: a suite of internal AI tools that change how our estimators quote, how our designers present, how our project managers communicate, and how our sales team closes.

These tools are already being built. What we need now is the engineer who takes them from individual applications to a unified, production-grade platform that our teams use every day; and who owns that platform long-term. This is not a startup. There is no runway pressure, no pivot risk, no "we might not make payroll." It is a stable, profitable company making a deliberate technology bet and giving one engineer the autonomy to define how it gets built.

WHAT YOU WILL OWN

The integration layer.

Multiple Claude-powered applications: estimating, proposal generation, project intelligence, client communication - need to function as one platform. Shared authentication, consistent data flow, clean service boundaries. You design that and you build it.

The infrastructure.

Provision and maintain the server environment these tools run on. Deployments that are repeatable. Environments that are consistent. Updates that do not break what is already working.

The security posture.

Access control, credential management, API key rotation, audit logging. Appropriate for internal enterprise tooling - correct and documented, not over-engineered.

The operational standard.

Logging, monitoring, alerting. Problems surface before users notice them. When something breaks, you fix it and you understand why it broke.

The feedback loop.

The people using these tools are designers, estimators, and project coordinators (not engineers). You will work directly with them, understand what they actually need, and translate that into product decisions.

This role is designed for an engineer with strong systems intuition and broad technical capability; not necessarily deep specialization in every domain. You will touch infrastructure, backend, security, and AI integration. The expectation is good judgment across all of them, not mastery of each.

Do you have experience in TLS?, LLM API integration - Production experience: prompt pipelines, error handling, cost management in a live environment.

Python or Node.js - Backend services, maintainable code. Able to work in and improve an existing codebase.

Linux server administration - SSH, permissions, firewall rules, process management. You have kept services running.

Docker in production - Containerize, deploy, and update without downtime.

Web security fundamentals - Authentication flows, secrets management, HTTPS/TLS, role-based access control.

GOOD TO HAVE / LEARNABLE

PostgreSQL - Schema design, multi-service connection management.

AWS or GCP basics - Compute, storage, networking fundamentals.

CI/CD pipelines - GitHub Actions or equivalent. Repeatable, usable by others.

Kubernetes - Useful, not required.

LangChain / LlamaIndex - Exposure counts, deep expertise not expected.

Bachelor's degree in Computer Science or a related engineering field, or equivalent professional experience in backend, infrastructure, or platform engineering systems.

Pulled from the full job description

• Health insurance
• Vision insurance
• Dental insurance
• Disability insurance
• On-site gym, BASE SALARY $105,000 - $130,000 Based on what you have built and kept running in production

Full Benefits Package: Medical, Dental, Vision, Life, Short Term Disability, Long Term Disability, On-Site Fitness Center and Paid Vacation/Personal Time Off.