AI Engineer

Requirements

• Work Authorization: USC / GC / EAD
• 10+ years experience
• Strong hands-on Python: production applications, REST APIs, automation and data-processing workflows (OOP, exception handling, unit testing, performance tuning)
• Cloud experience on AWS, Azure or GCP, plus Docker and Kubernetes, including deploying, troubleshooting and securing applications and AI/ML workloads
• Containerized platform services on Linux: Kubernetes deployments, configuration management, Bash scripting, networking and log analysis
• Secure APIs and identity services: authentication, authorization, secrets management and service-to-service integrations
• Git and CI/CD (GitHub Actions), with Terraform or Ansible for infrastructure automation, security scanning, controlled deployments and rollbacks
• Monitoring and observability with Splunk, Elasticsearch, Kibana, Prometheus and Grafana: dashboards, alerts and platform health

How to apply

• Send your updated resume along with your availability for a 30-minute screening call

Location

• Phoenix, AZ (Hybrid)