Azure Infrastructure Platform Engineer

CBTS; Chicago (IL); On-site; USD 55,000 - 96,000; Full time

Job summary

CBTS in Chicago seeks a hands-on Platform Engineer to design, deploy, and automate internal infrastructure services. You will build containerized apps with Docker and Kubernetes, automate installation and monitoring, and contribute to Git-based workflows and CI/CD pipelines.

You will integrate tools via REST APIs and messaging, implement robust observability, and help mature AI-enabled automation concepts across teams.

Qualifications

• 4+ years of hands-on platform engineering, DevOps, or related work.
• Practical Linux administration experience with commands, filesystems, and logs.
• Experience with container runtimes and orchestration (Docker, Kubernetes).
• Experience deploying APIs, web services, or automation workflows.
• Experience with Azure DevOps, YAML pipelines, and CI/CD processes.
• Familiarity with monitoring/observability tools (Grafana, Prometheus, etc.).
• Experience with MCP servers, AI agents, or tool-calling workflows is a plus.
• Ability to work independently and communicate progress clearly.

Responsibilities

• Design, deploy, configure, test, and document internal infrastructure platform services.
• Build and operate containerized applications using Docker, Docker Compose, Kubernetes, and related tools.
• Develop and maintain automation scripts for install, configure, validate, restore, and monitor platform services.
• Contribute production-quality code and docs via Git-based workflows and pull requests.
• Create and maintain Azure DevOps repos and CI/CD pipelines for internal tools and images.
• Integrate platforms through REST APIs, queues, YAML interfaces, and event-driven patterns.
• Implement monitoring and observability with health checks, dashboards, and alerts (Grafana/Prometheus).
• Design AI-enabled automation concepts and chat integrations with internal tools.

Skills

Linux admin

CI/CD

Git workflows

Automation

Observability

REST APIs

MCP servers

AI tooling

Tools

Docker

Docker Compose

Kubernetes

AKS

K3s

Minikube

Helm

Azure DevOps

Grafana

Prometheus

Uptime Kuma

Job description

Pay: Market Hourly Rate on W-2

Engagement Outcomes

• Deliver documented, supportable platform services and integrations aligned to agreed technical requirements.
• Improve repeatability through source control, CI/CD, automation, configuration standards, and operational runbooks.
• Establish practical monitoring, logging, alerting, backup, recovery, and lifecycle-management patterns for delivered services.
• Convert successful proofs of concept into secure, maintainable deployments that internal teams can operate.

Responsibilities

• Design, deploy, configure, test, and document internal infrastructure platform services.
• Build and operate containerized applications using Docker, Docker Compose, Kubernetes, AKS, K3s, or similar technologies as appropriate to the use case.
• Develop and maintain scripts and automation that installs, configures, validates, restores, upgrades, or monitors platform services.
• Contribute production-quality code, configuration, and documentation through Gitbased workflows, including branches, pull requests, peer review, issue tracking, and release practices.
• Create and maintain Azure DevOps repositories and CI/CD pipelines used to build, test, publish, and deploy internal tools and container images.
• Integrate infrastructure platforms through REST APIs, webhooks, message queues, JSON/YAML interfaces, scheduled jobs, or event-driven patterns.
• Implement monitoring and observability capabilities using health checks, metrics, logs, dashboards, and alerts with tools such as Uptime Kuma, Grafana, Prometheus, Azure Monitor, or equivalent platforms.
• Design and test AI-enabled automation concepts, including MCP servers, chatbot integrations, tool-calling workflows, local or hosted language models, retrieval systems, and internal assistants.
• Connect conversational interfaces to approved infrastructure tools and data sources while applying appropriate authentication, authorization, secrets management, and data-handling controls.
• Evaluate AI-assisted workflows for accuracy, reliability, security, traceability, and operational usefulness before recommending production use.
• Troubleshoot Linux services, containers, application logs, network connectivity, DNS, TLS certificates, permissions, identities, secrets, and configuration issues.
• Create architecture diagrams, deployment guides, operational runbooks, support procedures, validation plans, and handoff documentation.
• Own assigned engineering work from requirements through implementation and communicate progress, risks, blockers, results, and recommendations.
• Collaborate with network, server, cloud, cybersecurity, operational technology, and application teams.
• Follow CBTS requirements for security, access control, change management, data handling, and safe use of AI tools.

Requirements:

• 4+ years of hands-on experience in platform engineering, DevOps, systems engineering, software engineering, cloud engineering, or a closely related discipline.
• Practical Linux administration experience, including command-line tools, filesystems, permissions, processes, services, packages, networking, and logs.
• Hands-on experience with Docker or another container runtime and working knowledge of container orchestration concepts.
• Experience with Git-based development, code review, debugging, testing, documentation, and release workflows.
• Experience deploying or supporting APIs, web services, integrations, or automation workflows.
• Experience with Kubernetes, AKS, K3s, Minikube, Helm, or similar orchestration and packaging technologies.
• Experience with Azure DevOps repositories, build agents, work items, artifacts, and YAML pipelines.
• Experience with reverse proxies, TLS, DNS, authentication, managed identities, API tokens, RBAC, or secrets-management platforms.
• Experience with Infrastructure as Code, configuration management, automated testing, or policy-as-code practices.
• Experience operating monitoring or observability platforms such as Uptime Kuma, Grafana, Prometheus, Azure Monitor, Elastic, or equivalent tools.
• Hands-on experience with MCP servers, AI agents, locally hosted language models, chatbot integrations, retrieval systems, or tool-calling workflows.
• Experience moving a proof of concept into a documented, repeatable, monitored, and supportable production service.
• Experience supporting renewable energy, critical infrastructure, operational technology, or other highly available environments.
• Ability to troubleshoot across application, operating system, container, identity, certificate, and network layers.
• Ability to work independently, learn unfamiliar technologies through documentation and experimentation, and produce maintainable deliverables.
• Strong analytical, written, and verbal communication skills.

CBTS provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws.