DevOps Engineer
Havocai
| Company | Havocai |
| Category | Engineering |
| Location | United States |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 150k–185k |
| Posted | 10 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
ABOUT US:
Havoc is a leader in all-domain collaborative autonomy. Its software-defined hardware approach powers military and commercial-grade autonomous systems across sea, air, and land to sense, decide, and act together in complex and contested environments. Havoc connects assets, enabling them to share information, adapt in real time, and continue operating even when communications are disrupted or denied. Havoc optimizes mission performance and minimizes human risk.
Havoc was founded in 2024 and headquartered in Providence, Rhode Island. Learn more at Havoc: All-Domain Collaborative Autonomy http://havocai.com/ .
ABOUT THE ROLE
We are seeking a DevOps Engineer to join our Cloud Platform team and help build the infrastructure and tooling that powers our engineering organization.
In this role, you will focus on automation, CI/CD, and cloud infrastructure, enabling teams to build, deploy, and operate services reliably and efficiently. You will play a key role in creating paved paths and self-service tooling that improve developer velocity while maintaining high standards for reliability, security, and performance.
You will work closely with the Cloud Platform, SRE, and Data Engineering teams in a fast-paced environment where systems are built and tested in real-world conditions.
KEY RESPONSIBILITIES
AUTOMATION & PLATFORM ENABLEMENT
- Build and maintain CI/CD pipelines that support the full software development lifecycle
- Develop self-service tooling and standardized workflows for deployment and operations
- Improve developer experience through automation, documentation, and engineering best practices
- Help establish scalable platform capabilities that accelerate engineering teams
CLOUD INFRASTRUCTURE & OPERATIONS
- Implement and manage cloud infrastructure using Infrastructure as Code
- Deploy and support containerized workloads using Docker and Kubernetes
- Maintain and improve development, staging, and production environments
- Partner with Cloud Platform and SRE teams to ensure systems are scalable, reliable, secure, and cost-efficient
RELIABILITY, OBSERVABILITY & SECURITY
- Implement observability solutions across logging, metrics, tracing, and alerting
- Participate in incident response, root cause analysis, and continuous improvement efforts
- Implement secure CI/CD pipelines, secrets management, and access controls
- Contribute to operational readiness, reliability practices, and infrastructure resilience
CROSS-FUNCTIONAL COLLABORATION
- Partner with engineering teams to support deployment, infrastructure, and operational needs
- Troubleshoot infrastructure, deployment, and runtime issues across environments
- Contribute to platform standards, technical documentation, and engineering best practices
- Help improve engineering workflows through automation and collaboration
QUALIFICATIONS
- 3+ years of experience in DevOps, infrastructure, cloud platform, or related engineering roles
- Strong experience with CI/CD systems and deployment automation
- Hands-on experience with Docker and Kubernetes
- Experience managing cloud infrastructure, preferably AWS
- Familiarity with Infrastructure as Code tools such as Terraform or CloudFormation
- Experience operating production systems with monitoring, logging, and alerting
- Proficiency in scripting or programming languages such as Python, Bash, or Go
- Solid understanding of Linux systems and networking fundamentals
- Strong problem-solving skills and ability to work in a fast-paced environment
- Strong written and verbal communication skills
- U.S. citizenship and ability to obtain and maintain a U.S. Government security clearance if required
PREFERRED SKILLS
- Experience working on a cloud platform or internal developer platform
- Familiarity with Site Reliability Engineering (SRE) practices, including SLIs, SLOs, and error budgets
- Experience supporting data pipelines or analytics infras
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