Summary
✨ AI‑Generated
An experienced DevOps, Platform, Cloud, or SRE engineer is sought to build and operate scalable cloud infrastructure and containerized workloads. The role covers AWS, Kubernetes, infrastructure as code, CI/CD, observability, security, and automation, while providing a path toward AI and MLOps infrastructure.
Highlights
Hands-on infrastructure role focused on scalable AWS environments, Kubernetes, automation, observability, security, and CI/CD. Offers an opportunity to expand into AI and MLOps infrastructure while partnering closely with software and ML engineering teams.
Description
We’re looking for a DevOps Engineer to join CreatorIQ and help build, operate, and improve the cloud infrastructure behind our production applications and growing AI/ML capabilities.
You’ll work across AWS infrastructure, Kubernetes, CI/CD, Infrastructure as Code, observability, security, and automation.
You’ll also partner closely with Software and ML Engineers to support reliable deployment and operation of data- and ML-intensive workloads.
This is a great opportunity for an experienced DevOps, Platform, Cloud, or SRE engineer who enjoys hands-on infrastructure work and wants to grow further into AI and MLOps infrastructure.
What you’ll do
Build, maintain, and improve scalable and highly available AWS infrastructure.Manage containerized production workloads using Kubernetes and Amazon EKS.Provision and manage infrastructure using Terraform, Terragrunt, CloudFormation, or similar IaC tools.Build and maintain CI/CD pipelines using GitLab CI/CD, Jenkins, or similar technologies.Automate infrastructure provisioning, deployments, configuration, and operational processes using Python, Bash, and other automation tools.Improve system reliability through monitoring, logging, alerting, incident response, and root cause analysis.Implement cloud security and DevSecOps best practices across infrastructure and deployment workflows.Support production data, ML, and compute-intensive workloads.Partner with ML Engineering on infrastructure for ML pipelines, model deployment, model serving, and monitoring.Help operate and scale Databricks infrastructure, including clusters, jobs compute, ML pipelines, and Model Serving.Explore practical uses of AI-assisted engineering and agentic tooling to improve infrastructure management, troubleshooting, and operational efficiency.Participate in disaster recovery planning and help improve infrastructure reliability and cost efficiency.What we’re looking for
3+ years of experience in DevOps, Platform Engineering, Cloud Engineering, SRE, or a similar infrastructure-focused role.2+ years of hands-on AWS experience, including services such as EC2, S3, RDS, IAM, VPC, Lambda, SQS, or API Gateway.2+ years working with Kubernetes, ideally Amazon EKS.Strong hands-on experience with Terraform or another Infrastructure as Code technology.Experience building and maintaining CI/CD pipelines using Jenkins, GitLab CI/CD, or similar tools.Strong Linux administration and troubleshooting skills.Good understanding of networking, load balancing, IAM, and cloud security.Experience scripting and automating infrastructure tasks with Python, Bash, or similar languages.Experience supporting production data, ML, or other compute-intensive workloads.Hands-on experience using AI tools for engineering, automation, troubleshooting, or operational workflows.Nice to have
Experience with Databricks/MLOps, ML model serving, Prometheus/Grafana/Coralogix, Helm, service mesh technologies, GCP, FinOps, cloud security tooling, or API management platforms is a strong plus.
Compensation
$106,000–$127,000 USD/year
