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# Senior Cloud Infrastructure Engineer

- **Company:** LIGHTHOUSE
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $118,790.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Audit Trail, Microsoft Azure, Software as a Service, Cloud Computing, Software Quality, Continuous Integration, DevOps, Machine Learning, Software Tools, Cloud Services, Data Processing, Cloud Platform System, System Availability, AI Platforms, Kubernetes, Information Technology, Bicep, Api Design, Human in the Loop, Microservices
- **Published:** November 1, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ea3c04dd8eeda1fb

## About the Role

* Advanced expertise with Azure infrastructure, security, networking, and automation.
 * Expertise in Infrastructure as Code, including Terra form, ARM, and Bicep, and CI/CD workflows.
 * In-depth knowledge of Kubernetes administration, scaling, and monitoring.
 * Strong background supporting large-scale, distributed application hosting.
 * Proficiency in scripting and automation in multiple languages.
 * Practical experience using AI-assisted engineering tools to improve infrastructure-as-code quality, documentation, operational analysis, and developer workflows.
 * Understanding of responsible AI practices, including data handling, security, privacy, model limitations, human-in-the-loop review, and auditability.
 * Experience integrating or operating cloud AI services and API-based automation while applying least-privilege access, secret management, monitoring, and cost controls.
 * Ability to assess AI-generated technical output, validate it through testing and peer review, and prevent unsafe or unverified changes from reaching production.
 * Experience applying observability data, automation, and AI-assisted analysis to incident detection, response, and post-incident improvement.
 * Experience working within agile teams and influencing DevOps culture.
 * Excellent leadership, communication, and mentoring skills.
 * B.S. in Computer Science, Information Technology, Engineering, or a related field is required.
 * Microsoft Certified: Azure Solutions Architect Expert.
 * Certified Kubernetes Administrator (CKA).
 * 5-8 years of hands-on experience in cloud infrastructure engineering, including design, implementation, and maintenance of large-scale environments, preferably in Azure.
 * Demonstrated experience implementing automation and operational improvements in production cloud environments.
 * Experience with AI-enabled engineering or cloud AI services is preferred.

## Description

The Senior Cloud Infrastructure Engineer demonstrates deep technical expertise and leadership in cloud infrastructure, automation, application hosting, and AI-enabled engineering practices. This role designs robust, scalable cloud solutions that align with business and security requirements; mentors engineers; and applies AI responsibly to improve delivery, operations, and reliability.

What will this person do?

 * Lead the design and implementation of complex Azure infrastructure solutions, ensuring scalability, security, reliability, and cost efficiency.
 * Champion Infrastructure as Code and automation across all environments, establishing best practices and standards.
 * Architect, configure, and optimize Kubernetes clusters for high availability, security, and performance.
 * Collaborate with cross-functional teams to support microservices architectures and application modernization.
 * Build and improve CI/CD pipelines, operational tooling, and observability practices.
 * Leverage AI-assisted tools to accelerate infrastructure design, code authoring, documentation, troubleshooting, and knowledge sharing, with appropriate human review
 * Design secure, governed patterns for using AI services in infrastructure workflows, including identity, access control, data protection, auditability, and cost management.
 * Apply AI and machine-learning-enabled observability to identify anomalies, correlate signals, prioritize incidents, and improve root-cause analysis
 * Evaluate AI-enabled automation opportunities and implement measurable improvements to reliability, engineering productivity, and operational response
 * Lead incident response efforts, conduct post-mortems, and drive continuous improvement initiatives
 * Mentor associate and regular engineers on cloud tools, AI-enabled workflows, troubleshooting, and responsible engineering practices
 * Participate in agile leadership activities, including story grooming and technical reviews.