> Markdown version of [/jobs/ext/4255251-senior-cloud-infrastructure-engineer](https://www.wearedevelopers.com/jobs/ext/4255251-senior-cloud-infrastructure-engineer). 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).

---

# Senior Cloud Infrastructure Engineer

- **Company:** CHAOS Industries
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $140,000 - $240,000
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Computing Platforms, Microsoft Azure, Cloud Computing, Cloud Computing Security, Databases, Distributed Systems, Domain Name System (DNS), Subnetting, Python (Programming Language), Key Management, PostgreSQL, Routing, OAuth, OpenID, Queueing Systems, Redis, Data Streaming, WebSocket, Datadog, Pulumi, Google Cloud, Load Balancing, Cloud Platform System, Caching, Backend, AWS ECS, Cloudformation, Fastapi, Data Layers, Kubernetes, Bicep, AWS Fargate, Cosmos DB, Terraform, Docker, Container Apps
- **Published:** October 26, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0bb1f09f1f94e2e3

## About the Role

* Have built and operated production infrastructure in at least one major cloud - Azure, AWS, or GCP - defined in code with Terraform, Pulumi, Bicep, or CloudFormation.
 * Have run containerized production workloads (Docker) on a managed platform such as Azure Container Apps, AWS ECS or Fargate, Google Cloud Run, or Kubernetes.
 * Have strong cloud networking fundamentals: virtual networks, subnets, routing, DNS, load balancers, private endpoints, and firewalls.
 * Have built and operated production backend services in Python, Go, or a similar language, and understand what happens under load - concurrency, async I/O, connection pooling, and resource limits.
 * Are fluent in distributed systems: consistency and replication, partitioning, caching, back-pressure, idempotency, and how systems fail - and how to design so that they degrade gracefully.
 * Have scaled a production system well beyond its original design, and fixed what broke on the way.
 * Build securely by default - least-privilege access, secrets kept out of code, and patched, hardened systems - and can explain the trade-offs behind those choices.

## Description

You'll join a small, highly collaborative team in San Francisco building the cloud platform behind some of the world's most advanced radar systems. You'll design, build, and operate both the infrastructure and the backend services that move mission-critical sensor data from radars in the field to the operators who depend on it. The platform is in production and growing fast, and your job is to scale it as our fleet of sensors, customers, and deployments grows., * Cloud Infrastructure - design and operate our Azure infrastructure as code with Terraform: networking, Azure Container Apps, managed databases, and the CI/CD pipelines that deploy to them.

 * Backend Platform Services - build and own high-throughput Python (FastAPI) services and the data layer behind them (PostgreSQL/TimescaleDB, Redis, Cosmos DB) that ingest and stream real-time sensor data.
 * Platform Architecture - work with engineering teams across the company to define the architecture of the next generation of the platform.
 * Operations - own security, reliability, and observability across the platform: identity and access, secrets management, network isolation, monitoring and alerting (Datadog), and incident response., * Azure Government, AWS GovCloud, or other regulated environments (FedRAMP, CMMC, NIST 800-171 or 800-53).
 * Real-time and streaming data systems: WebSockets, server-sent events, pub/sub, and message queues.
 * Identity and cloud security: Entra ID, OAuth 2.0 / OIDC, managed identities, service-to-service authentication, and policy as code.