> Markdown version of [/jobs/ext/4616779-software-engineer-cloud-infrastructure](https://www.wearedevelopers.com/jobs/ext/4616779-software-engineer-cloud-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Software Engineer, Cloud Infrastructure

- **Company:** DATOLOGY, INC.
- **Location:** Redwood City, CA, United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Bash Shell, Big Data, Cloud Computing, Cloud Engineering, Software Code Optimization, Software Debugging, Python (Programming Language), Network Troubleshooting, Machine Learning, Memory Leaks, Pulumi, Data Processing, Cloud Platform System, System Availability, Multi-Cloud, HybridCloud, Cloudformation, Kubernetes, Machine Learning Operations, Terraform
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25197_5d2ecad7df6435e1c75b8262bd3e17fd

## About the Role

You've led or helped build robust infrastructure systems at a startup or fast-moving engineering organization

Deep experience working with cloud providers (especially AWS), and ideally 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

You're 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

## Description

We're looking for an experienced Cloud Infrastructure Engineer to join our core team at DatologyAI. In this role, you will lead the design, build, and operation of highly available, secure, and scalable cloud infrastructure that powers our training, inference, and data curation pipelines. You'll work closely with engineering, research, and product teams to define how we deploy and manage compute resources across AWS and other cloud providers. This role is a key early hire and offers an opportunity to have a deep technical and cultural impact.

What You'll Work On

Architect and maintain our 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

Drive cost-efficiency strategies across compute and storage resources

Respond to and resolve infrastructure-related incidents with a sense of ownership and urgency