DevOps / MLOps Engineer
Summary
Remote DevOps/MLOps engineer at MacroCoderz running cloud infrastructure, CI/CD pipelines and monitoring for production AI systems, LLM services and vector databases across AWS, GCP and Azure. The focus is keeping AI workloads reliable, secure and cost-efficient, including LLM cost tracking.
Remote DevOps / MLOps Engineer at MacroCoderz: run cloud infrastructure, CI/CD and monitoring for production AI systems, LLM services and vector databases.
AI systems bring infrastructure problems of their own: model endpoints with unpredictable latency, vector databases that grow fast, GPU workloads, and API bills that need watching. As a DevOps / MLOps Engineer you keep all of it reliable, secure and affordable.
You own environments across AWS, GCP and Azure, the pipelines that ship code and models, and the monitoring that tells us something is wrong before a client does.
What you will do
- Build and maintain CI/CD pipelines for application code, prompts and models.
- Provision cloud infrastructure as code.
- Run containers and services reliably in production.
- Set up monitoring, logging, alerting and LLM cost tracking.
- Apply security practices: secrets management, access control, backups and patching.
What we are looking for
- 3+ years running production workloads on AWS, GCP or Azure.
- Strong Linux, Docker and a CI/CD tool such as GitHub Actions or GitLab CI.
- Infrastructure as code with Terraform, Pulumi or similar.
- Scripting in Bash or Python.
Nice to have
- Kubernetes experience.
- Has deployed GPU workloads, model servers or vector databases.
- Observability tools such as Grafana, Prometheus or Datadog.
Location
fully remote, open to applicants worldwide.
