Software Engineer

Revenera helps product executives build better products, accelerate time to value and monetize what matters.  Revenera’s leading solutions help software and technology companies drive top line revenue with modern software monetization, understand usage and compliance with software usage analytics, empower the use of open source with software composition analysis and deliver an excellent user experience—for embedded, on premises, cloud, and SaaS products.

Job Description:

Software Engineer - Kubernetes & Cloud Optimization

Role Overview

We are looking for a Software Engineer with strong Kubernetes development experience to join the Rightsizing team. The engineer will design, develop, and enhance cloud-native optimization capabilities that help customers improve Kubernetes resource utilization, reduce infrastructure costs, and automate workload optimization.

The ideal candidate should be comfortable developing backend services, working with Kubernetes APIs, building cloud-native solutions, and solving scalability and optimization challenges in large Kubernetes environments. The role involves hands-on product development, not cluster administration alone. The engineer will work on features such as workload rightsizing, auto scaling integrations, cost optimization, resource recommendations, GPU optimization, and workload automation

Experience

Software Engineer

• 2 - 4 years of software development experience.
• 2+ years of hands-on Kubernetes development experience.
• Strong coding and debugging skills.

Key Responsibilities

Product Development

• Design and develop backend services supporting Kubernetes workload optimization and rightsizing.
• Build scalable micro services and APIs that interact with Kubernetes clusters.
• Develop recommendation engines for CPU, memory, storage, and workload optimization.
• Implement support for vertical and horizontal workload rightsizing.
• Enhance integrations with Kubernetes auto scaling frameworks including HPA, KEDA, and cloud-native scaling services.
• Develop features related to replica optimization, workload savings analysis, and resource allocation.

Kubernetes Engineering

• 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.

Cloud Optimization

• 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.

Engineering Excellence

• 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.

Required Technical Skills

Kubernetes (Must Have)

• 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.

Development Skills (Must Have)

• Strong coding experience in one or more: Java, Python
• Experience building APIs and distributed systems.
• Experience with Microservices architecture.
• Strong knowledge of data structures and algorithms.

Cloud Platforms

• Experience: AWS(Must Have), Azure, GCP
• Knowledge of: EKS, AKS, GKE

Containers & DevOps

• Docker, Helm, Git, GitHub Actions / Jenkins, Terraform

Databases

• PostgreSQL, MySQL, MongoDB, Redis (Nice to have)

Observability

• Experience with: Prometheus, SumoLogic, Grafana, OpenTelemetry, ELK

Preferred Qualifications

• Experience developing Kubernetes Operators or Controllers.
• Experience with workload autoscaling technologies (HPA, KEDA, VPA).
• Knowledge of FinOps and cloud cost optimization.
• Understanding of workload recommendation engines.
• Experience with AI/ML-driven optimization or recommendation systems.
• Exposure to GPU scheduling and optimization.
• Experience building highly scalable SaaS products.

Revenera is proud to be an equal opportunity employer.  Qualified applicants will be considered for open roles regardless of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by local/national laws, policies and/or regulations.  Regarding disability, we encourage candidates requiring accommodations to please let us know by emailing careers@flexera.com.