Top Remote Cloud Engineer Jobs

Design and scale distributed systems for Ditto's edge-to-cloud capabilities, lead services development in Rust, and mentor engineers.

Implement and support DNS and Kubernetes architecture in a private cloud environment, ensuring scalability, resilience, and performance optimization through IaC tools, while collaborating with teams and managing incidents.

Nagarro is seeking an experienced Principal Engineer for cloud-focused initiatives, emphasizing innovative and strategic contributions in a non-hierarchical environment.

Senior hands-on engineer responsible for designing, deploying, and supporting Azure and hybrid cloud infrastructure. Lead Azure IaaS implementations, hybrid integrations, incident escalations, MSP oversight, automation with PowerShell/Azure CLI, and operational documentation for enterprise and manufacturing/edge-connected workloads.

Lead hands-on development of scalable, secure enterprise applications. Partner with business stakeholders to design and deliver full-stack solutions using Python, React/Next.js, REST APIs, microservices, and cloud platforms (AWS). Work with enterprise data platforms (Snowflake, Databricks, PostgreSQL, SQL Server) to prototype and productionize impactful software.

Design, build, and maintain Terraform-based multi-account cloud infrastructure; create CI/CD pipelines; develop automation workflows and AI-assisted engineering tools; monitor observability and security posture with Datadog; eliminate operational toil via scripting, IaC, and AI tooling while ensuring compliance.

Design, develop, test, deploy, and sustain secure enterprise applications for DCSA using Java/Kotlin/TypeScript and Oracle/SQL Server in AWS GovCloud. Participate in SDLC, Agile teams, code reviews, CI/CD, documentation, compliance with federal security requirements, and deliver stakeholder briefings.

Design, build, and operate a scalable, highly available cloud-native infrastructure for ClickHouse Cloud. Lead optimization initiatives across compute, storage, and networking, automate cloud resource management, collaborate with engineering and business stakeholders, and deliver cost-efficient, secure distributed systems and tooling for a global SaaS platform.

Design, build, and automate secure cloud environments and platforms in AWS/Azure. Develop Python-based automation, Infrastructure as Code modules (Terraform/OpenTofu/CloudFormation), and CI/CD pipelines. Troubleshoot provisioning and security issues, mentor engineers, lead technical initiatives, and partner with application teams to adopt cloud engineering best practices in an Extreme Programming, paired-programming environment.

Design and implement secure, resumable cloud pipelines to ingest multi-terabyte medical imaging data; build GPU-accelerated orchestration with strong retry semantics and cost controls; define data lifecycle and retention; implement HIPAA/PHI security and compliance controls; and deliver operational tooling (monitoring, alerting, runbooks) for a device fleet.

Design and own CI/CD and configuration management for a large-scale, multi-cluster Kubernetes fleet. Define GitOps-driven, declarative reference architectures and templated production environments. Implement progressive delivery (canary, automated rollback), improve pipeline reliability and speed, evolve the Internal Developer Portal, embed AI tooling into delivery workflows, and partner with Cloud, Security, and Compliance while mentoring senior engineers.

Lead design, operation, and evolution of AlphaSense’s cloud and Kubernetes platform. Improve security, reliability, cost, and performance; build tooling and AI integrations; enable self-service workflows; support global engineering teams and drive platform standards and automation.

The Cloud and Storage Engineer designs and implements SAN architecture, manages storage solutions, and ensures system uptime while supporting federal agency requirements.

Develop and implement Storage Area Network architecture for a large EMC-based infrastructure, address performance, capacity, security, and manage disaster recovery efforts. Design storage solutions and provide capacity planning, troubleshooting, and technical documentation to ensure optimal operation.

The Cloud and Storage Engineer will develop SAN architecture, manage storage infrastructure, and ensure uptime, while performing security tasks.

The Cloud and Storage Engineer designs and implements SAN architecture, manages storage capacity, performs complex troubleshooting, and ensures continuous uptime in a cloud environment.

Cloud and Storage Engineer responsible for developing and implementing SAN architecture, managing storage solutions, optimizing performance, and ensuring 24/7 infrastructure uptime for government services.

The Cloud and Storage Engineer develops and implements SAN architecture, ensures system uptime, manages backup solutions, and addresses complex storage issues.

The Cloud and Storage Engineer will develop and implement SAN architecture, manage storage solutions, ensure 24/7 uptime, and troubleshoot complex issues while working on security tasks and technical documentation.

The Cloud and Storage Engineer will design and implement EMC-based SAN architectures, manage storage systems, ensure security compliance, and optimize storage solutions.

The Cloud and Storage Engineer designs and implements SAN architecture, manages infrastructure, optimizes storage solutions, and performs security tasks for a federal agency.

The Cloud and Storage Engineer will develop and implement SAN architecture, manage storage requirements, troubleshoot issues, and produce technical documentation.

The Principal Cloud Infrastructure Engineer will design, analyze, and maintain cloud infrastructure, ensuring compliance with security standards and integrating application development with IT infrastructure.

The Senior Cloud Engineer will design and manage cloud infrastructures, support migrations, automate provisioning, and ensure cloud security while mentoring junior engineers.

The GPU Cloud Platform Engineer designs and operates multi-cluster GPU infrastructures for AI workloads, ensuring performance and efficiency across cloud environments.