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H2O.ai

No-code AutoML platform for AI/ML

Software Engineer - DevOps

Cloud EngineeringConfirmed live in the last 24 hours
Full-timeSydney NSW, AustraliaNo salary listed

About the Job

Requirements

  • A degree in Computer Science, Information Technology, or a related discipline, or equivalent practical experience.
  • At least 2 years of experience in cloud, DevOps, platform engineering, or related roles.
  • At least 2 years of hands-on software development experience using Python, Java, or Go, including writing and maintaining production application code beyond internal tooling and automation.
  • Strong hands-on coding skills and production application development experience.
  • Strong hands-on experience with AWS.
  • Experience deploying cloud-based applications.
  • Experience building CI/CD pipelines and automating infrastructure.
  • Troubleshooting skills across Linux, containers, networking, and distributed systems.
  • Written and verbal communication skills.
  • Ability to learn and adapt quickly in a fast-moving environment.

Responsibilities

  • Deploy, maintain, and improve secure, scalable systems on AWS and Kubernetes.
  • Automate infrastructure provisioning and configuration using Infrastructure as Code tools such as Terraform, Ansible, and CloudFormation.
  • Support reliability, performance, security, and scalability of customer cloud environments.
  • Implement cloud security best practices across IAM, networking, encryption, and access controls.
  • Design and maintain CI/CD pipelines for reliable software delivery.
  • Automate operational processes and environment provisioning.
  • Implement observability frameworks including metrics, logging, monitoring, and alerting.
  • Manage release and configuration processes for production systems.
  • Deploy and operate production-grade Kubernetes clusters.
  • Troubleshoot and optimize containerized workloads using tools such as kubectl, Helm, ingress controllers, and cloud-native services.
  • Work directly with enterprise customers and partners to support deployments and operational improvements.
  • Translate technical requirements into practical implementation plans.
  • Contribute to architecture discussions and continuous improvement recommendations.
  • Support incident resolution and troubleshooting across cloud and Kubernetes environments.
  • Collaborate with internal teams to surface product feedback and improve the deployment experience.

Desired Qualifications

  • Prior experience in customer-facing technical roles within banking or financial services is highly advantageous.
  • Experience with Infrastructure as Code tools such as Terraform, Ansible, and CloudFormation.
  • Experience with Kubernetes and container orchestration.
  • Experience with CI/CD tools such as GitHub Actions, Jenkins, or GitLab CI.
  • Experience with monitoring and observability tools such as Prometheus, Grafana, and cloud-native monitoring.
  • Knowledge of cloud security fundamentals.
  • Experience scripting with Bash, Python, or similar.
  • Exposure to GCP or Azure.
  • Cloud, Kubernetes, or AI/ML certifications.
  • Experience supporting AI/ML or data-intensive workloads.
  • Familiarity with security, compliance, or data governance requirements.
  • Exposure to generative AI frameworks such as LangChain, AutoGen, MiroFish, or OpenClaw.

About the Company

H2O.ai

No-code AutoML platform for AI/ML

H2O.ai provides AI and ML solutions for businesses, with Driverless AI as its core AutoML platform. It automates feature engineering, model building, visualization, and interpretability to help users create predictive and generative models with minimal coding. The platform supports information retrieval, data labeling and processing, no-code deep learning, and emphasizes data security, plus a platform to develop, deploy, and share trusted AI apps. Its goal is to help organizations of all sizes accelerate data-driven decisions and scale secure AI deployment, differentiating through accessible AutoML, enterprise-grade security, and a strong talent base that includes Kaggle Grandmasters.

Company size
201-500
Company stage
Series E
Total funding
$251.1M
Headquarters
Mountain View, CA
Founded
2012

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