AI Engineer
Galaxy i Technologies, Inc
Phoenix, AZ, United States
4 days ago
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Role details
Contract type
Contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Amazon Web Services
Build Automation
Automation of Tests
Unit Testing
Microsoft Azure
Bash Shell
Command-Line Interface
Configuration Management
Continuous Integration
Linux
+23 more
Elasticsearch
Github
Python (Programming Language)
Key Management
Log Analysis
Object-Oriented Software Development
Performance Tuning
Ansible
Prometheus
Data Logging
Data Processing
Google Cloud
Grafana
Git
Kubernetes
Infrastructure Automation Frameworks
Machine Learning Operations
Kibana
Restful APIs
Terraform
Splunk
Docker
Vulnerability Analysis
Requirements
- Strong hands-on Python experience building reliable, maintainable production applications, REST APIs, automation scripts, and data-processing workflows, with proficiency in object-oriented programming, exception handling, unit testing, and performance optimization.
- Hands-on experience with at least one major cloud platform-AWS, Azure, or Google Cloud-and with Docker and Kubernetes, including deploying, troubleshooting, and securing applications and AI/ML workloads.
- Experience designing and operating containerized platform services on Linux, including Kubernetes deployments, configuration management, and troubleshooting across environments, with strong skills in Bash scripting, command-line tools, process and service management, networking, and log analysis.
- Experience building and maintaining secure APIs and identity-related services, including authentication, authorization, secrets management, and service-to-service integrations.
- Strong experience with Git, CI/CD tools such as GitHub Actions, and infrastructure automation using Terraform or Ansible, including automated builds, testing, security scanning, controlled deployments, and rollback procedures.
- Hands-on experience with monitoring, logging, and observability tools such as Splunk, Elasticsearch, Kibana, Prometheus, and Grafana to query logs, collect metrics, build dashboards, configure alerts, and monitor application and platform health.
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