Software Engineer

ProsperOps

. Design and develop backend services supporting Kubernetes workload optimization and rightsizing .

Posted 10/7/2026full-timeBangalore • IndiaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Kubernetes development, including building scalable microservices and APIs, optimizing workloads, and implementing autoscaling frameworks. Proficient in coding with Java or Python, and experienced in cloud environments such as AWS, Azure, and GCP.

Highest-signal resume keywords

Kubernetes DevelopmentMicroservices ArchitectureAPI DevelopmentCloud Cost OptimizationWorkload Scheduling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

JavaPythonKubernetes APIsData StructuresAlgorithmsWorkload OptimizationDistributed SystemsKubernetes OperatorsAutoscaling TechnologiesSaaS Product Development

Soft Skills

Coding SkillsDebugging Skills

Tools & Technologies

DockerHelmGitGitHub ActionsJenkinsTerraformPrometheusGrafanaOpenTelemetryELK

Industry Keywords

EKSAKSGKEFinOpsAI/ML Optimization

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDockerGoogle Cloud PlatformGrafanaJavaJenkinsKubernetesMicroservicesPrometheusPythonTerraform

About the role

Key responsibilities & impact

Design and develop backend services supporting Kubernetes workload optimization and rightsizing
Build scalable microservices and APIs that interact with Kubernetes clusters
Develop recommendation engines for CPU, memory, storage, and workload optimization
Implement vertical and horizontal workload rightsizing
Enhance integrations with Kubernetes autoscaling frameworks including HPA, KEDA, and cloud-native scaling services
Develop features related to replica optimization, workload savings analysis, and resource allocation
Work with Kubernetes APIs, controllers, operators, and CRDs
Develop and maintain integrations with EKS, AKS, and GKE
Build telemetry and observability capabilities to collect workload utilization metrics
Investigate cluster behavior and optimize resource allocation algorithms
Develop solutions that improve workload efficiency and reduce cloud spend
Build capacity planning, forecasting, and recommendation capabilities
Support GPU optimization, workload scheduling, bin-packing, and resource allocation initiatives
Contribute to rightsizing features across AWS, Azure, and Kubernetes environments
Participate in design reviews and architecture discussions
Write clean, maintainable, well-tested code
Create automated unit, integration, and performance tests
Contribute to CI/CD pipelines and deployment automation
Troubleshoot production issues and participate in operational support rotations

Requirements

What you’ll need

2–4 years of software development experience
2+ years of hands-on Kubernetes development experience
Strong coding and debugging skills
Strong understanding of Kubernetes architecture, Pods, Deployments, StatefulSets, Services and Ingress, ConfigMaps and Secrets, Namespaces, RBAC, HPA and Cluster Autoscaling
Hands-on experience using Kubernetes APIs
Experience troubleshooting Kubernetes applications and workloads
Understanding of workload scheduling and resource allocation
Strong coding experience in Java or Python
Experience building APIs and distributed systems
Experience with microservices architecture
Strong knowledge of data structures and algorithms
Experience with AWS
Experience with Azure and GCP
Knowledge of EKS, AKS, and GKE
Experience with Docker, Helm, Git, GitHub Actions or Jenkins, and Terraform
Experience with Prometheus, SumoLogic, Grafana, OpenTelemetry, or ELK
Experience developing Kubernetes Operators or Controllers preferred
Experience with workload autoscaling technologies (HPA, KEDA, VPA) preferred
Knowledge of FinOps and cloud cost optimization preferred
Understanding of workload recommendation engines preferred
Experience with AI/ML-driven optimization or recommendation systems preferred
Exposure to GPU scheduling and optimization preferred
Experience building highly scalable SaaS products preferred

Benefits

Comp & perks

Fully remote team
100% of roles open to applicants anywhere in the region in which the role is advertised
Equal opportunity employer
Reasonable accommodations available for candidates who require them