Infrastructure Engineer

The client is a US healthcare-data company building a platform for pharmacy benefit managers. The platform ingests historical patient and prescription data, runs it through an ETL pipeline into a unified data model, and serves machine-learning models that produce drug and treatment recommendations. Today the process is manual — data prepared on a desktop, models deployed by hand, no CI/CD. The goal is a production SaaS platform with a first MVP at the end of 2026. The infrastructure is AWS, with Docker and Kubernetes as the runtime, and a strong preference for open-source tooling over managed proprietary services. The availability target is 99.9%, 24×7. Current usage is proof-of-concept scale, so the design has to reach that target without over-building, and cost must be a design input from day one: an environment that meets the checklist but whose bill doubles in six months is not acceptable. This is a full-time, remote engagement. Working hours are 06:00–14:00 US Eastern, and development happens on client-provided virtual desktops. Key Responsibilities - Design the AWS and Kubernetes infrastructure for the platform from the target architecture, and document it. - Build the environments — development, test and production — with clear separation and repeatable provisioning. - Set up CI/CD from scratch for application code, data pipelines and model deployments. - Define infrastructure as code and keep every environment reproducible from it. - Design for 99.9% availability, 24×7: monitoring, alerting, backups, recovery and on-call practice. - Own cost: choose instance types, storage and scaling policies deliberately, and report on spend. - Put security and access controls in place appropriate to sensitive healthcare data. - Work with the data engineer to run pipelines and model services reliably on Kubernetes. - Replace manual deployment steps with automated, auditable ones. - Propose an approach and defend it rather than waiting for a fully formed requirement. - Write the runbooks and documentation the team needs to operate the platform without you in the room. Required Qualifications - DevOps or platform engineering experience, including ownership of a production environment. - Hands-on AWS experience. - Hands-on Docker and Kubernetes experience in production. - Experience building CI/CD pipelines from scratch. - Infrastructure as code with a tool such as Terraform, and the discipline to keep environments reproducible. - Experience designing for and operating to a defined availability target, including monitoring, alerting and incident response. - Demonstrated cost-conscious design and cost management in a cloud environment. - Real C1 English, role requires direct client meetings without an intermediary. - Availability during 06:00–14:00 US Eastern. Preferred Qualifications - Experience running data pipelines and machine-learning workloads on Kubernetes. - Experience with an open-source observability stack (Prometheus, Grafana, Loki or similar). - Security and compliance experience with healthcare or other regulated data. - Experience with GitOps tooling such as Argo CD or Flux. - Experience with Python or scripting for automation. - Experience taking a proof-of-concept environment to production. Your First 90 Days - First 30 days — You have reviewed the target architecture, produced the infrastructure design with a cost estimate, and agreed it with the CTO; a first environment is provisioned from code. - By 60 days — Development and test environments run from infrastructure as code, CI/CD deploys the data pipeline and model services without manual steps, and monitoring and alerting are live. - By 90 days — Production is running to the availability target with backups and recovery tested, spend is tracked against the estimate, and the runbooks exist for someone else to operate the platform.