Senior Platform Engineer

ResponsibilitiesWe are seeking a Senior Platform Engineer with expertise in supporting Kubernetes and Kafka across on-premises and multi-cloud environments (Azure, GCP). The ideal candidate will also be eager to learn about and assist with integrating edge computing platforms, enabling AI technology stacks, and utilizing a robust DevOps toolset. This role requires hands-on Kubernetes experience and a strong foundation in modern platform solutions. Kubernetes Management: Provision, manage, and maintain Kubernetes clusters in on-premises and cloud environments (Azure, GCP). Serverless & Service Mesh: Deploy and manage Knative for serverless workloads and Istio for service mesh implementations. Custom Kubernetes Development: Create custom Kubernetes operators and controllers using Go to extend Kubernetes functionality. Edge & AI Integrations: Integrate edge computing platforms with AI/ML workloads (e.g., TensorFlow Serving, PyTorch, Kubeflow) for efficient edge processing. Collaboration: Work closely with AI/ML, data engineering, and platform teams to optimize resource utilization and scalability for edge and AI workloads. Kafka Administration: Build and administer Kafka clusters to support Kafka Connect in containerized environments. Handle partitioning strategies and optimize Kafka performance. Automation & Provisioning: Develop Ansible playbooks for infrastructure automation and platform provisioning. CI/CD Pipelines: Design and implement GitOps workflows using Jenkins and GitHub/GitLab, ensuring continuous integration and deployment. Monitoring & Logging: Implement robust monitoring with Prometheus and Grafana, and manage centralized logging via ELK or Fluentd. Optimization & Troubleshooting: Apply best practices for performance, platform resilience, and disaster recovery. Diagnose complex issues related to Kafka pipelines, Kubernetes orchestration, and CI/CD processes. Core Skills Kubernetes (5+ years): Cluster management, deployments, Helm charts, operators, and scaling/integrations. Service Mesh: Working knowledge of Istio or Linkerd for secure microservices communication. Edge Computing: Experience with platforms such as Azure IoT Edge, AWS Greengrass, or GCP Edge TPU is a plus. AI/ML Infrastructure: Experience deploying AI/ML workloads (e.g., TensorFlow Serving, PyTorch, Kubeflow). Cloud Platforms: Hands-on experience with at least two of Azure or GCP. Terraform & Ansible: Proficient in infrastructure provisioning and configuration management. CI/CD: Familiarity with Jenkins, GitHub Actions, GitLab, or similar tools. Go (Golang) / Python: Ability to develop Kubernetes-native solutions (operators, CRDs, controllers). Kafka: Knowledge of Kafka cluster setup, topic management, partitioning, broker optimization, and Kafka Connect is beneficial. Monitoring & Logging: Expertise with Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana), or Fluentd. Benefits If you’re ready for responsibility, you’ve come to the right place. At beON, your experience truly counts. We offer: Competitive Compensation: Attractive salary, bonus opportunities, and salary increases based on experience. Professional Growth: Ongoing development and learning through advanced technology stacks, mentorship from experts, and external resources. Newest IT Innovation: Opportunities to expand your IT expertise Support & Resources: Access to innovative tools and environment you need to succeed. Positive Culture: An appreciative atmosphere centered on transparency, fairness, and enjoyment at work. Contact Us We look forward to hearing from you