Accountabilities:

Cloud Infrastructure and Platform Engineering: Design, build, and operate scalable cloud infrastructure that supports production applications and enterprise platforms.
Develop and maintain cloud landing zones, networking configurations, identity management, security controls, and environment management processes.
Implement and manage infrastructure-as-code solutions to standardize provisioning, configuration, and infrastructure lifecycle management.
Build and maintain Kubernetes environments and containerized workloads to support reliable application deployment and operation.
CI/CD and Deployment Automation: Develop and optimize continuous integration and continuous deployment pipelines to enable secure, consistent, and automated software delivery.
Establish repeatable deployment practices and infrastructure workflows that improve engineering efficiency and reduce operational complexity.
Support deployments across cloud, hybrid, Bring Your Own Cloud (BYOC), on-premises, customer-controlled, and edge environments.
Site Reliability and Observability: Establish and maintain comprehensive observability capabilities, including metrics, logs, traces, dashboards, alerting, and actionable operational insights.
Define and support Service Level Objectives (SLOs), reliability standards, production readiness practices, and operational performance monitoring.
Lead or contribute to incident response, troubleshooting, root cause analysis, postmortems, and on-call operations.
Identify potential reliability risks and implement improvements that strengthen system availability, resilience, and performance.
Automation and Operational Excellence: Automate repetitive operational tasks through scripting, internal tools, runbooks, and reusable platform services.
Reduce manual workloads and operational toil while improving deployment consistency and engineering productivity.
Develop standardized infrastructure capabilities that can be reused across multiple teams, products, and customer environments.
Cost and Capacity Optimization: Monitor infrastructure usage, resource consumption, and system capacity to identify opportunities for optimization.
Improve infrastructure cost efficiency, particularly for resource-intensive environments involving GPUs and other specialized computing workloads.
Balance performance, scalability, reliability, security, and infrastructure costs when making technical decisions.
Customer and Cross-Functional Collaboration: Collaborate with engineering teams, platform specialists, and client stakeholders to understand infrastructure requirements and deliver effective solutions.
Provide technical guidance and support for complex customer deployments, including regulated, air-gapped, hybrid, and mission-critical environments.
Contribute to infrastructure architecture decisions and help teams prepare applications for reliable production operation.
Use AI-assisted development tools where appropriate while maintaining rigorous standards for code quality, testing, security, and operational reliability.

Requirements

Demonstrated professional experience building and operating production cloud infrastructure, with direct responsibility for system reliability and operational performance.
Strong expertise in infrastructure-as-code, including cloud landing zones, networking, identity and access management, security, and environment configuration.
Hands-on experience with Kubernetes, containerized applications, CI/CD pipelines, and automated deployment practices.
Strong understanding of observability practices, including metrics, centralized logging, distributed tracing, dashboards, alerting, and operational monitoring.
Experience defining or supporting Service Level Objectives (SLOs), reliability engineering practices, incident management, postmortems, and on-call operations.
Proficiency in scripting and automation, with the ability to develop tools, runbooks, and reusable solutions that reduce manual operational work.
Experience managing cloud infrastructure and production environments, with a strong understanding of scalability, availability, performance, and security.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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