PREVENT DISASTER. PROTECT HUMANITY.

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Location: San Francisco, CA — On-site ONLY

Start: Immediate

Estimated TC: up to ~$250,000

Cash Compensation: $160,000–$230,000

Position: DevOps Engineer

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We are on a mission to safeguard humanity, create American resilience, and neutralize catastrophic Category 5 hurricanes.

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Aeolus is working on a problem that has historically lived at the edge of government-scale science: understanding, predicting, and eventually weakening the most destructive storms before they reach land. We are building the modeling, sensing, simulation, and field-engineering stack needed to turn hurricane intervention from a research frontier into an operational capability.

Our team brings together atmospheric science, cloud physics, ML weather modeling, high-performance simulation, aerospace systems, environmental sensing, and software engineering. We are small enough that every major system still has a clear owner, but ambitious enough that our work touches problems normally reserved for national labs, weather agencies, and large aerospace programs.

We are now seeking an exceptional DevOps Engineer to own the infrastructure layer beneath all of this: the cloud environments, deployment systems, CI/CD, infrastructure-as-code, and scalable compute systems that let a deeply technical 22-person team move with the leverage of a much larger organization.

DevOps Engineer:

You will take ownership of the cloud infrastructure, deployment systems, and compute environments that power Aeolus’s scientific, ML, and engineering work. You’ll be the technical foundation our scientists, ML engineers, software engineers, and operations teams build on — designing and operating the cloud environments, CI/CD pipelines, infrastructure-as-code, and scalable compute systems that keep our platform reliable, secure, cost-efficient, and fast.

Responsibilities

Cloud Infrastructure Ownership: Own and operate our cloud infrastructure across AWS, GCP, and other compute providers, ensuring reliability, security, scalability, and cost efficiency
Infrastructure-as-Code: Lead the development and maintenance of Terraform-based infrastructure across development, staging, research, and production environments
CI/CD & Deployment Systems: Design and operate CI/CD pipelines that enable fast, safe, reproducible delivery of our modeling, data, and software systems
Cloud Architecture: Guide architectural decisions for cloud deployments and establish reusable patterns, best practices, and guardrails for the engineering team
Containers & Runtime: Manage containerized workloads, including Docker image builds, container registries, runtime environments, and orchestration across AWS/GCP infrastructure
HPC & GPU Compute: Build and maintain scalable compute environments for HPC and GPU workloads, including cluster management, job scheduling, provisioning, and cost-aware scaling
Observability & Reliability: Implement metrics, logging, tracing, alerting, dashboards, and runbooks across our infrastructure stack
Data Infrastructure Support: Partner with software engineers and scientists to optimize infrastructure for processing massive meteorological, satellite, radar, and simulation datasets
Security & Governance: Drive security, IAM, networking, compliance, secrets management, and cost governance across our cloud footprint
Developer Enablement: Make the infrastructure easy for scientists and engineers to use without sacrificing reliability, reproducibility, or operational discipline

Qualifications

BS/MS in Computer Science, Engineering, or related technical field, or equivalent practical experience
Strong hands-on experience with AWS and GCP, including compute, networking, storage, IAM, VPCs, and security groups
Deep proficiency with Terraform and infrastructure-as-code in production environments
Experience designing, operating, and improving CI/CD systems such as GitHub Actions, GitLab CI, or similar tools
Solid understanding of containerization and orchestration, including Docker and Kubernetes or equivalent systems
Experience managing Linux systems, shell scripting, networking, permissions, secrets, and production operational workflows
Strong judgment around reliability, security, cost, and developer velocity
Ability to work directly with scientists, ML engineers, and software engineers to translate messy technical requirements into durable infrastructure

Technical Expertise

Cloud Platforms: AWS, GCP, and multi-cloud infrastructure patterns
Infrastructure-as-Code: Terraform, reusable modules, environment management, state management, and secure provisioning
CI/CD: GitHub Actions, GitLab CI, automated testing, deployment workflows, artifact management, and release discipline
Containers: Docker, container registries, Kubernetes or equivalent orchestration systems
HPC/GPU: GPU provisioning, cluster management, job scheduling, high-throughput compute environments, and cost-aware scaling
Networking & Security: VPCs, IAM, security groups, service accounts, secrets, access control, and production security hygiene
Observability: Metrics, logs, tracing, alerting, dashboards, incident response, and operational runbooks

Nice to Have

Experience with HPC environments and job schedulers such as SLURM, AWS ParallelCluster, or similar systems
Familiarity with GPU compute infrastructure, including provisioning, scheduling, utilization tracking, and cost management
Experience with container runtimes for HPC, including Apptainer/Singularity, Pyxis, or enroot
Background working with scientific, meteorological, geospatial, or data-intensive workloads
Experience supporting large-scale data pipelines, model training, simulation workloads, or numerical computing systems
Knowledge of serverless and event-driven architectures such as AWS Lambda, GCP Cloud Run, Modal, or similar platforms
Familiarity with workflow orchestration platforms such as Dagster, Airflow, or Prefect
Prior work in research-oriented, field-oriented, defense, aerospace, scientific computing, or safety-critical environments
Experience with cost optimization, cloud financial controls, and FinOps practices, Infrastructure & Platform Craft
You care about clean infrastructure, reproducible environments, strong defaults, and systems that other engineers can actually use.
You know when to move fast and when to slow down and build the right operational foundation.
You are comfortable working across cloud infrastructure, scientific computing, CI/CD, security, and production reliability.
You can operate in ambiguity, make pragmatic tradeoffs, and build systems that support both research velocity and real-world deployment.

Willingness To:

Work in person five days a week in San Francisco
Build infrastructure for an early-stage company attempting something extremely hard
Work closely with atmospheric scientists, ML engineers, software engineers, controls engineers, and field teams
Support systems that may eventually power real-world flight operations and weather intervention missions
Move quickly without losing operational discipline
Help build the infrastructure backbone for a company trying to stop environmental disaster

Compensation & Benefits

Cash compensation: $160,000–$230,000 depending on experience and level

Estimated total compensation: up to ~$300,000

Benefits: Full health, dental, and vision insurance

PTO: Flexible PTO

Location: In-person role based in San Francisco, CA

This position is centered on building the infrastructure that powers Aeolus’s modeling, data, simulation, and intervention systems. You’ll work shoulder-to-shoulder with our scientific, engineering, and operational teams to deliver robust, scalable, field-ready capability.

To apply, please fill out the application and email your resume and a brief note about why you’re interested in Aeolus to: jobs@aeolus.earth

Aeolus

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