Cloud Infrastructure Engineer

About the Role DatologyAI is seeking an experienced Cloud Infrastructure Engineer to lead the design, build, and operation of highly available, secure, and scalable multi-cloud infrastructure powering our training, inference, and data curation pipelines. You will collaborate with engineering, research, and product teams to define how we deploy and manage compute resources across AWS and other cloud providers. What You'll Do

• Architect and maintain multi-cloud infrastructure (primarily AWS, potentially Azure/GCP), with a focus on reliability, security, and scalability
• Define and implement infrastructure-as-code best practices using Terraform, CloudFormation, Pulumi (and similar technologies)
• Design and manage Kubernetes-based systems for model training, inference, and data processing workloads
• Optimize our CI/CD pipelines and streamline deployment of services across environments
• Build monitoring, alerting, and logging systems to ensure high system availability and observability
• Collaborate with research and engineering teams to provide infrastructure support for training large-scale ML models
• Ensure our infrastructure supports various deployment models (cloud, on-prem, hybrid) for enterprise use cases
• Drive cost-efficiency strategies across compute and storage resources
• Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency What We're Looking For
• 4+ years of relevant experience and a track record leading or helping build robust infrastructure at a startup or fast-moving engineering organization
• Deep experience with cloud providers (especially AWS), with exposure to multi-cloud or hybrid-cloud setups
• Strong with Kubernetes, Terraform, and containerized architectures
• Confident with systems-level debugging—networking issues, memory leaks, resource bottlenecks, etc.
• Comfortable writing clean, maintainable scripts in Bash, Python, or Go
• You care deeply about building secure and scalable systems and take pride in reliable infrastructure
• Collaborative, humble, and ready to own high-impact projects end-to-end Nice to Have
• Experience supporting infrastructure for ML workloads (training pipelines, inference clusters, GPU orchestration)
• Built or scaled infrastructure for teams working with large-scale datasets
• Exposure to cost monitoring and optimization tools in cloud environments
• Background supporting compliance and security in enterprise deployments Compensation & Benefits
• Salary: $180,000 - $300,000 per year
• 100% covered health benefits (medical, vision, and dental)
• 401(k) plan with a generous 4% company match
• Unlimited PTO policy
• Paid Parental Leave of 12 weeks, plus 6 months of WFH flexibility
• Annual $2,000 wellness stipend
• Annual $1,000 learning and development stipend
• Daily lunches and snacks provided in our office
• Relocation assistance for employees moving to the Bay Area