About the Company:

Everest DX – We are a Digital Platform Services company, headquartered in Stamford. Our Platform/Solution includes Orchestration, Intelligent operations with BOTs’, AI-powered analytics for Enterprise IT. Our vision is to enable Digital Transformation for enterprises to deliver seamless customer experience, business efficiency and actionable insights through an integrated set of futuristic digital technologies.

Digital Transformation Services - Specialized in Design, Build, Develop, Integrate, and Manage cloud solutions and modernize Data centers, build a Cloud-native application and migrate existing applications into secure, multi-cloud environments to support digital transformation. Our Digital

Platform Services enable organizations to reduce IT resource requirements and improve productivity, in addition to lowering costs and speeding digital transformation.

Digital Platform - Cloud Intelligent Management (CiM) - An Autonomous Hybrid Cloud Management Platform that works across multi-cloud environments. helps enterprise Digital Transformation get most out of the cloud strategy while reducing Cost, Risk and Speed.

To know more please visit: http://www.everestdx.com

Experience: 5–10 Years

Role Type: Platform Engineering / Cloud-Native Infrastructure

Work Mode: Hybrid / In office, as per project requirements

Role Overview

We are seeking a Platform Engineering Engineer to design, develop, automate, and enhance enterprise-scale cloud-native platforms. The role involves building reusable infrastructure capabilities, enabling application teams through self-service platforms, and implementing secure, scalable, observable, and reliable environments across public cloud and on-premises infrastructure.

Key Responsibilities

- Design, build,



and maintain Kubernetes-based platforms across multi-cluster and hybrid-cloud environments.
- Develop and maintain platform automation, Infrastructure as Code (IaC), and CI/CD pipelines.
- Implement DevSecOps practices, policy-as-code, security controls, and automated compliance checks.
- Configure and integrate observability solutions for metrics, logs, traces, alerting, and performance monitoring.
- Develop reusable platform components, self-service workflows, and golden paths for application teams.
- Implement container networking, service mesh, ingress, load balancing, and cluster lifecycle management.
- Design and manage cloud storage, persistent volumes, backup, recovery, and data protection capabilities.
- Build and maintain GPU-enabled infrastructure and platform services supporting AI/ML and LLM workloads.
- Integrate cost-management and FinOps capabilities to optimize cloud and infrastructure consumption.
- Collaborate with application, security, SRE, and architecture teams to establish platform standards and best practices.
- Troubleshoot complex platform issues, improve reliability, and document architectural decisions and operational procedures.

Required Technical Skills

1. Kubernetes & Cloud Platforms

- Strong hands-on experience with Kubernetes, Docker, Helm, and container orchestration.
- Experience with Amazon EKS, Azure AKS, and other Kubernetes distributions.
- Knowledge of multi-cluster management, Rancher, K3s, RKE2,



and hybrid-cloud/on-premises deployments.

2. DevOps & Automation

- Expertise in CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or equivalent.
- Infrastructure as Code using Terraform, Ansible, or similar tools.
- Strong scripting skills in Python, Bash, or Go.
- GitOps practices and automated configuration management.

3. Security & Policy Management

- Experience with RBAC, IAM, secrets management, image scanning, and container security.
- Familiarity with policy-as-code tools such as Kyverno or Open Policy Agent (OPA).
- Understanding of Kubernetes network policies and compliance automation.

4. Observability & APM

- Experience with Prometheus, Grafana, Elastic Stack, OpenTelemetry, or equivalent.
- Knowledge of application performance monitoring, distributed tracing, log aggregation, and alerting.

5. Networking & Storage

- Knowledge of Kubernetes networking, CNI, ingress controllers, DNS, and service mesh technologies such as Istio.
- Experience with persistent storage, cloud storage integrations, CSI drivers, and backup/recovery solutions.

6. Cost Management & AI Infrastructure

- Familiarity with Kubecost, Flexera, or similar cloud cost-management platforms.
- Understanding of GPU infrastructure, NVIDIA technologies, and resource scheduling for AI/ML workloads.
- Exposure to LLM hosting, AI agents, and Model Context Protocol (MCP) is an advantage.

Preferred Qualifications

- Experience building internal developer platforms or platform-as-a-product capabilities.
- Exposure to self-hosted build agents, COTS application platforms, stateful applications, and IoT edge workloads.
- Relevant cloud or Kubernetes certifications are desirable.
- Strong problem-solving, documentation, and cross-functional collaboration skills.

📌 Platform Engineering Engineer (Hyderabad)
🏢 EverestDX
📍 Hyderabad