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# Platform Engineer, AI Infrastructure

- **Company:** Focused Labs
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $145,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Microsoft Azure, Cloud Computing, Continuous Integration, Software Debugging, DevOps, Python (Programming Language), OpenAI, Azure Machine Learning, Runbook, Software Deployment, Software Engineering, AI Infrastructure, Scripting, Enterprise Software Applications, LangChain, Large Language Models, Llamaindex, Agentic-AI, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Azure AKS, Machine Learning Operations, Hardware Infrastructure, Terraform
- **Published:** November 6, 2026
- **Apply:** https://www.careerbuilder.com/job-details/platform-engineer-ai-infrastructure-chicago-il--abd471b8-6497-4db7-ba13-7a5034224df7

## About the Role

Artificial Intelligence (AI), Channel Strategies, Software Design, Diving, Problem Solving Skills, Cloud Computing, Enterprise Applications, Electrical Wiring, Artificial Intelligence (AI), Software Engineering, * 5+ years in platform, infrastructure, DevOps, or SRE roles

 * Hands-on production experience with Kubernetes
 * Experience with Azure and/or GCP
 * Experience with Terraform or similar IaC tools
 * Experience supporting AI/ML platforms or ML workloads in production
 * Proficiency in Python plus solid scripting skills

Preferred Qualifications (Exceptional Candidates):

 * Experience building LLM applications or agents (LangChain, LangGraph, LlamaIndex, or similar)
 * Experience with Azure OpenAI or Vertex AI
 * Familiarity with GPU infrastructure and model serving
 * Consulting or client-facing experience

## Description

Platform & Infrastructure

 * Build and operate Kubernetes clusters on Azure AKS and GCP GKE
 * Write and maintain Terraform modules for cloud resources and environments
 * Build CI/CD and GitOps pipelines for platform and application deployments
 * Monitor, troubleshoot, and improve the reliability of AI/ML platform services

AI Platform Engineering & Operations

 * Deploy and operate supporting services for LLM applications: model gateways, vector databases, tracing, and evaluation
 * Support GPU workloads, including node pools, scheduling, and cost monitoring
 * Write runbooks and automate day-two operations

AI Engineering

 * Build reference agents and LLM application templates that client teams can start from
 * Help application teams integrate with the platform and debug their workloads
 * Prototype with agent frameworks and LLM APIs to test what the platform needs to support, * You've shipped an LLM feature or agent to real users, not just a demo
 * You enjoy pairing and learn quickly from senior engineers
 * You build documentation systems that auto-update for the next person (and coding agent)