Job Url: https://www.linkedin.com/jobs/search/?currentJobId=4341423525&f_AL=true&f_TPR=r86400&f_WT=2&keywords=software%20engineer&origin=JOB_SEARCH_PAGE_JOB_FILTER&start=150

Job Description: What You’ll Build

Design and implement an AI-powered toolkit integrated with Large Language Models (LLMs) and Retrieval Augmented Generation (RAG), built to support hybrid IT environments. This comprehensive toolkit will empower technical support teams across areas including:

Kubernetes Fundamentals: Pods, deployments, namespaces, eviction, and network policies 
Virtualization: OpenShift Virtualization, KVM, and VM orchestration 
Mixed Workload Management: Best practices for managing VMs + containers 
Resource Optimization: Memory, CPU, and storage allocation across workloads 
Networking & Integration: Kubernetes networking, UDNs, F5 SPK 
Persistent Storage & Fault Tolerance: Storage tuning, replication, and HA strategies 
Live Migration: Seamless VM/database migration with uptime focus 
Automation: Provisioning, scaling, orchestration in Webscale environments 
AI/LLM Tooling: Contextual retrieval, chatbot pipelines, and automation flows 
Troubleshooting & Updates: Real-time log analysis and system patching 
Custom Configurations: Tailored networking/storage for enterprise deployments 
High Availability: Resilient design for fault-tolerant multi-platform systems 

Ideal Candidate Profile

Deep experience in Kubernetes, OpenShift 4.18, and virtualization stacks 
Proficiency in designing AI/LLM-based tools, particularly RAG frameworks 
Strong understanding of support enablement systems and documentation standards 
Self-motivated, autonomous, and comfortable with remote contract work 
Capable of translating complex systems into AI-powered assistive tools