Cloud Engineer

NeevSys Inc.

Vienna, United States

15 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

neevsys.com

Tech stack

Artificial Intelligence Amazon Web Services Amazon S3 Microsoft Azure Bash Shell Cloud Computing Cloud Database Cloud Engineering Configuration Management Databases Continuous Integration Data as a Services

+16 more

DevOps Amazon DynamoDB Python (Programming Language) SQL Azure Windows PowerShell Cloud Services Multi-Cloud Cloudformation Amazon Relational Database Service Core Data Kubernetes Bicep Cosmos DB Terraform Data Pipelines Docker

Job description

Design, provision, and manage cloud infrastructure across AWS and Azure.
Author and maintain infrastructure as code (Terraform, CloudFormation, ARM / Bicep) and configuration management.
Configure networking, security, identity, and environments across both platforms.
Integrate and operate cloud data services (managed databases, storage, data pipelines, analytics) in both AWS and Azure.
Support reliability, security, cost, and observability of the cloud estate.

Requirements

Hands-on production experience in both AWS and Azure - not just one.
Strong infrastructure-as-code skills (Terraform and/or native CloudFormation / ARM / Bicep).
Configuration management and environment automation.
Working knowledge of each cloud’s core data services (AWS RDS / DynamoDB / S3 / Redshift / Glue; Azure SQL / Cosmos DB / Data Factory / Synapse / Storage).
Solid scripting (Python, PowerShell, or Bash) and CI/CD familiarity.
US work authorization; clearance eligibility per contract environment.

Preferred

Containers and orchestration (Docker, Kubernetes / EKS / AKS).
Experience supporting AI / data-intensive or secure government cloud workloads.
Certifications (AWS Solutions Architect / DevOps; Azure Administrator / Solutions Architect).

About the company

Neevsys is currently seeking an experienced multi-cloud engineer who stands up and manages infrastructure across both AWS and Azure, codifies it as infrastructure as code, and integrates each platform’s managed data services to support data- and AI-intensive workloads.