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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
