AI Cloud Engineer: Must be local to Austin, TX, on-site job
We are seeking a talented and innovative AI Cloud Engineer to join our team. As part of the AI Technical Team, you will design, build, and deploy AI cloud applications and support AI cloud platforms using cloud native services. This includes troubleshooting application, infrastructure, networking, and performance-related issues in cloud environments.
If you are passionate about artificial intelligence and innovation, we’d love to hear from you!
- Collaborate with cross-functional teams to deliver scalable and secure solutions.
- Integrate AI tools and techniques into application workflows for automation, predictive analytics, and intelligent features.
- Participate in code reviews, ensure adherence to best practices, and mentor junior developers.
· Troubleshoot and resolve complex technical issues across the stack.
Minimum Yrs of Experience, Skills, and Qualifications
Years of Experience - Qualifications
Strong hands-on experience designing, building, and supporting cloud-native applications on AWS
Proficiency with core AWS services such as Lambda, API Gateway, ECS/Fargate, EC2, S3, DynamoDB, IAM, VPC, and CloudWatch
Experience developing, deploying, and maintaining scalable, highly available, and secure cloud solutions.
Expertise in troubleshooting application, infrastructure, networking, and performance-related issues in cloud environments.
Experience creating and maintaining CI/CD pipelines using tools such as AWS CodePipeline, GitLab CI/CD, Jenkins, or similar platforms.
Proficiency with Infrastructure as Code (IaC) technologies such as Terraform, CloudFormation, or AWS CDK.
Strong understanding of cloud networking concepts including VPCs, load balancers, DNS, routing, security groups, and connectivity troubleshooting.
Experience with containerization and orchestration technologies such as Docker and Fargate (ECS preferred).
Strong scripting and automation skills using Python, PowerShell, Bash, or similar languages to improve operational efficiency.
Knowledge of cloud security, monitoring, logging, and operational best practices, including IAM, observability, incident response, and performance optimization.
Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch) or AI-powered development tools (e.g., GitHub Copilot, ChatGPT-based coding assistants).
Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform) and containerization (Docker/Kubernetes).
Understanding of CI/CD pipelines and version control (Git)
