Cloud Platform Engineer

Job Description

Job Description

Jumpmind is looking for a Cloud Platform Engineer who is passionate about building infrastructure, automating deployments, and delivering a reliable platform for running our microservices. This is a hands-on engineering role focused on Kubernetes orchestration, AWS infrastructure automation, and platform enablement for Jumpmind Commerce , which powers seamless customer journeys for some of the largest retailers in the world.

You will work closely with development, DevOps, and SRE teams to create a scalable, secure, and self-service cloud platform that helps our teams deliver faster with confidence.

Roles and Responsibilities

Design, build, and maintain Kubernetes-based infrastructure to run and scale microservices.

Automate provisioning, configuration, and management of AWS resources using Terraform .

Develop internal tooling and workflows that simplify environment creation and deployments.

Build and maintain CI / CD pipelines with GitHub Actions to streamline delivery of platform changes.

Collaborate with engineering teams to embed observability and best practices into all platform components.

Contribute to infrastructure architecture decisions, security hardening, and performance tuning.

Document infrastructure patterns, automation scripts, and processes for team-wide adoption.

Essential Skills and Qualifications

3+ years of experience in cloud infrastructure development, platform engineering, or DevOps roles.

Strong expertise with Kubernetes (workload deployment, Helm, autoscaling, ingress).

Hands-on experience with AWS (EKS, ECS, EC2, RDS, S3, IAM, VPC networking).

Proficiency with Terraform (or similar infrastructure-as-code tools).

Experience building automation and CI / CD workflows (preferably GitHub Actions ).

Flexible in technology stack and willing to learn

Solid understanding of cloud networking, security, and scalability best practices.

Preferred Experience

Running and supporting Java / Spring microservices in Kubernetes.

Experience tuning clusters for performance and cost efficiency.

Familiarity with observability tools ( CloudWatch, OpenTelemetry, Grafana ).

Knowledge of service mesh technologies (Istio, Linkerd) and advanced Kubernetes networking.

Exposure to incident response and root cause analysis for platform issues.