Senior Cloud Infrastructure Engineer

Job summary

This senior engineering role leads the design and operation of secure, scalable Azure infrastructure, using automation, application hosting, and responsible AI-enabled practices to improve reliability and delivery. The work includes setting Infrastructure as Code and Kubernetes standards, developing CI/CD and observability capabilities, supporting microservices modernization, leading incident response, and mentoring engineers. Technologies include Azure, Terraform, ARM, Bicep, Kubernetes, and cloud AI services.

Benefits

Qualifications

• 5–8 years of hands-on cloud infrastructure engineering experience, 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 preferred.
• Advanced Azure infrastructure, security, networking, and automation expertise.
• Expertise with Terraform, ARM, Bicep, and CI/CD workflows.
• In-depth Kubernetes administration, scaling, and monitoring knowledge.
• Experience using AI-assisted engineering tools and applying responsible AI practices.
• Ability to validate AI-generated technical output through testing and peer review.
• Experience applying observability data, automation, and AI-assisted analysis to incident management.
• Experience working in agile teams and influencing DevOps culture.

Responsibilities

• Lead design and implementation of secure, scalable, reliable, and cost-efficient Azure infrastructure.
• Establish Infrastructure as Code and automation standards.
• Architect, configure, and optimize Kubernetes clusters.
• Support microservices architectures and application modernization with cross-functional teams.
• Build and improve CI/CD pipelines, operational tooling, and observability.
• Use AI-assisted tools for infrastructure design, coding, documentation, troubleshooting, and knowledge sharing, with human review.
• Establish secure, governed patterns for AI use in infrastructure workflows.
• Apply AI-enabled observability to detect anomalies, correlate signals, prioritize incidents, and support root-cause analysis.
• Evaluate AI-enabled automation and improve reliability, engineering productivity, and operational response.
• Lead incident response, conduct post-mortems, and drive continuous improvement.
• Mentor engineers on cloud tools, AI-enabled workflows, troubleshooting, and responsible engineering.
• Participate in story grooming and technical reviews.

Skills

Certifications

Degrees

Work schedule

Relocation