DevOps Engineer
- Role
- DevOps
- Experience
- Senior
- Employment
- Full-time
- Company size
- Startup
Open to LB only. Set where you work from to check your eligibility.
No BS summary
DevOps Engineer needed to build and manage cloud infrastructure (AWS, GCP, Azure) for an AI product. Requires 4+ years of experience, strong cloud provider knowledge, IaC proficiency, containerization/orchestration skills, CI/CD experience, scripting, and a security-first mindset. Experience with AI/ML workloads and cost optimization is a plus.
Core skills
Required skills
Optional skills
About the Role We're looking for a DevOps Engineer to build the infrastructure foundation that keeps our AI-powered product fast, reliable, secure, and cost-efficient. You'll set up the cloud, deployment, and monitoring systems that let a small team ship confidently and scale smoothly through the pilot and beyond. What You'll Do Design, provision, and manage cloud infrastructure (AWS, GCP, or Azure) Build and maintain CI/CD pipelines for fast, safe, automated deployments Implement infrastructure-as-code (Terraform, Pulumi, or similar) for reproducible environments Containerize and orchestrate services (Docker, Kubernetes) as the system grows Set up observability: monitoring, logging, alerting, and tracing across the stack Manage and optimize the cost, latency, and reliability of LLM and AI workloads Own security, secrets management, and access controls across environments Establish backup, disaster-recovery, and incident-response practices for the pilot
4+ years of DevOps, SRE, or infrastructure engineering experience Strong hands-on experience with at least one major cloud provider (AWS/GCP/Azure) Proficiency with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation) Experience with containerization and orchestration (Docker, Kubernetes) Solid CI/CD experience (GitHub Actions, GitLab CI, CircleCI, or similar) Strong scripting skills (Bash, Python, or Go) Experience implementing monitoring and observability tooling (Prometheus, Grafana, Datadog, etc.) Security-first mindset and experience with secrets and access management
Experience managing infrastructure for AI/ML or LLM-heavy workloads Familiarity with cost optimization for high-throughput API usage Experience with GPU infrastructure or inference serving Early-stage experience standing up infrastructure from scratch
What you'll do
- Design, provision, and manage cloud infrastructure (AWS, GCP, or Azure)
- Build and maintain CI/CD pipelines for fast, safe, automated deployments
- Implement infrastructure-as-code (Terraform, Pulumi, or similar) for reproducible environments
- Containerize and orchestrate services (Docker, Kubernetes) as the system grows
- Set up observability: monitoring, logging, alerting, and tracing across the stack
- Manage and optimize the cost, latency, and reliability of LLM and AI workloads
- Own security, secrets management, and access controls across environments
- Establish backup, disaster-recovery, and incident-response practices for the pilot
What they require
- 4+ years of DevOps, SRE, or infrastructure engineering experience
- Strong hands-on experience with at least one major cloud provider (AWS/GCP/Azure)
- Proficiency with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation)
- Experience with containerization and orchestration (Docker, Kubernetes)
- Solid CI/CD experience (GitHub Actions, GitLab CI, CircleCI, or similar)
- Strong scripting skills (Bash, Python, or Go)
- Experience implementing monitoring and observability tooling (Prometheus, Grafana, Datadog, etc.)
- Security-first mindset and experience with secrets and access management
A rapidly growing business operating in AI-powered marketing and automation.