I help teams run production systems that stay online, whether they live in the cloud, on Kubernetes, or on bare-metal servers handling massive state and data. I’m a Senior Site Reliability / DevOps Engineer with 8+ years of hands-on experience operating infrastructure across AWS, GCP, Azure, DigitalOcean, and bare-metal environments. My work goes far beyond deployments — I design, operate, and recover systems where downtime, data corruption, or slashing are real risks. What I do in practice • Operate bare-metal servers (disk layout, RAID, IO tuning, recovery) • Run blockchain validator / RPC / full / archive nodes in production • Design safe Kubernetes architectures (StatefulSets, leader election, autoscaling trade-offs) • Keep large PostgreSQL systems stable under heavy load • Build monitoring that detects real failures, not just “pod is up” • Automate ops workflows using Go and Python Blockchain & validator experience I run and maintain validator node services, where reliability and correctness matter more than raw throughput: Validator and RPC node setup and maintenance Safe handling of upgrades, restarts, and snapshots Monitoring block height, peer health, syncing state, and reorgs Avoiding data corruption and slashing risks Designing leader-based consumption where horizontal scaling is unsafe This includes both cloud-based and bare-metal deployments, depending on performance and cost requirements.

I am an AI Systems Engineer focused on building production-grade intelligent systems using machine learning, large language models, and multimodal AI. I design systems that can understand, generate, and act on data across text, audio, and visual inputs — moving beyond static automation into real-time, decision-capable AI systems. I specialize in taking AI from concept → architecture → production, building complete systems that integrate models, data pipelines, and scalable backends. 🧠 CORE AI EXPERTISE Generative AI & LLM Systems • Retrieval-Augmented Generation (RAG) using vector embeddings and real-time data • LLM-powered copilots, assistants, and automation systems • Context-aware AI applications with memory and dynamic reasoning Multimodal AI Systems • Document intelligence (OCR → structured data pipelines) • Speech systems (Speech-to-Text, Text-to-Speech) • Voice cloning and audio synthesis systems • Cross-modal pipelines combining text, audio, and visual data Machine Learning Systems • End-to-end ML pipelines (training, deployment, inference) • Time-series forecasting and predictive modeling • Anomaly detection and intelligent monitoring systems 🚀 AI SYSTEMS BUILT Multimodal AI Platform (Audio + Document Intelligence) Designed and deployed a unified AI system integrating: • AI OCR Scanner → Converts PDFs and images into structured text • Speech-to-Text → Multi-language transcription (125+ languages) • Text-to-Speech → Natural audio generation (17+ languages) • Voice Cloning → High-accuracy voice replication → Enables voice assistants, document automation, accessibility tools, and conversational AI systems AI FinOps Intelligence System (Enterprise Scale) • ML-based cost prediction using NeuralProphet, Darts, CatBoost • Recommendation systems using ML + vector similarity • LLM-powered assistants for real-time operational insights AIVault — AI Content Authenticity Platform • Multi-modal AI detection across image, video, audio, and text • Real-time verification system for enterprise use cases • AI + backend system design for scalable deployment Highway Guard — Computer Vision System • Real-time detection using deep learning (YOLO-based models) • Processes live visual data for intelligent monitoring and decision-making 📊 IMPACT • Built AI systems operating at large-scale, production environments • Automated workflows using LLMs, reducing effort from days to minutes • Designed real-time AI systems handling high concurrency workloads • Delivered AI-driven systems improving efficiency, accuracy, and automation ⚡ HOW I WORK I approach problems as a systems engineer, not just a model builder: • Define the problem from a data + system perspective • Design appropriate ML / LLM architectures • Build end-to-end pipelines (data → model → API → product) • Optimize for scalability, performance, and real-world reliability 🎯 HOW I CAN HELP YOU AI PRODUCT DEVELOPMENT • LLM apps (RAG, copilots, assistants) • Multimodal AI systems (text, audio, vision) • AI-powered automation tools END-TO-END AI SYSTEMS • Model → backend → APIs → deployment • Scalable AI architecture design • Production-ready AI systems (not prototypes) ➤ LET’S BUILD SOMETHING REAL If you're building an AI system that needs to work reliably in production — not just a demo — I can help you design and implement it end-to-end. Message me to discuss your project.

Delivers exceptional IT solutions through DevOps, Cloud Expertise, and Full-Stack Development. Key Skills: - DevOps & Automation: Git, Jenkins, Docker, Kubernetes, CI/CD implementation. - Cloud Infrastructure: AWS (EC2, EB, ECS, EKS, Lightsail, S3, CodePipeline, CodeBuild, Lambda, CloudWatch, Route53, LB, RDS, and more), DigitalOcean, GCP. - MERN Stack Development: MongoDB, Express, React, and Node.js for building fast, scalable, and responsive full-stack web applications. - Linux Administration: Ubuntu, Debian, CentOS, AlmaLinux, RockyLinux. - Web Experience (Deployment & Optimization): WordPress, Laravel, Angular, React, Django (WP Perf). - Site Reliability Engineering (SRE): Prometheus, Grafana, Graylog, ELK, AppDynamics, and Moogsoft (for proactive monitoring and management). - Project Management: Jira & Google Workspace. - Web Servers: Nginx, Apache, HAProxy, OpenLiteSpeed. - Email Servers: Postfix, Exim, iRedMail, Relay. - Migration: Website, Database, Infrastructure, Platform (including WHM/cPanel and other control panels). Contact me to discuss your IT needs!

Cloud infrastructure becomes expensive, unstable, and hard to manage when it grows faster than the systems around it. I help teams build, fix, automate, migrate, and optimize cloud environments across GCP, AWS, Kubernetes, Terraform, CI/CD, Linux, and monitoring. I’m a Top Rated Plus Cloud & DevOps Engineer with hands-on experience helping startups and engineering teams improve cloud reliability, reduce cloud costs, automate deployments, and move from manual infrastructure to production-ready cloud systems. My strongest cloud platforms are Google Cloud Platform and AWS. I work across both environments and can help with cloud architecture, Kubernetes, infrastructure automation, CI/CD pipelines, migrations, system administration, cost optimization, and security hardening. I usually get called in when: — GCP or AWS infrastructure is misconfigured, unstable, or difficult to manage — Cloud Run, Cloud SQL, Compute Engine, EC2, ECS, EKS, or Kubernetes workloads need troubleshooting — Cloud costs are increasing and the team needs optimization without breaking production — Terraform exists, but the infrastructure needs better structure, automation, or cleanup — CI/CD pipelines are unreliable, manual, or missing proper deployment automation — Applications need to be migrated between cloud providers or from servers to cloud-native infrastructure — Linux servers, Docker, Kubernetes, or cloud networking issues are slowing the team down — Teams need a reliable DevOps engineer who can investigate problems and fix them quickly What I can help with: GCP & AWS Cloud Infrastructure Designing, deploying, troubleshooting, and improving cloud environments using Google Cloud Platform and Amazon Web Services, including Compute Engine, Cloud Run, Cloud SQL, Cloud Build, IAM, service accounts, VPC, EC2, ECS, EKS, RDS, S3, Route53, CloudWatch, and related services. Kubernetes & Containers Docker, Kubernetes, Helm, EKS, GKE, containerized deployments, service configuration, ingress, autoscaling, troubleshooting, and production workload support. Terraform & Infrastructure as Code Terraform-based infrastructure automation, reusable modules, environment setup, infrastructure cleanup, remote state, cloud resource provisioning, and repeatable deployment workflows. CI/CD & DevOps Automation GitHub Actions, Jenkins, Bitbucket Pipelines, Cloud Build, Azure DevOps, Docker builds, automated deployments, release pipelines, and deployment troubleshooting. Cloud Cost Optimization Reviewing GCP and AWS usage to identify oversized resources, idle services, expensive databases, inefficient workloads, storage waste, and opportunities to reduce monthly cloud spend. Linux & System Administration Ubuntu, CentOS, Red Hat, Nginx, Apache, Bash scripting, server setup, migration, monitoring, security updates, SSL, DNS, and troubleshooting production server issues. Security & Reliability IAM review, service account permissions, secrets handling, network security, backup readiness, monitoring, logging, alerting, access control, and production reliability improvements. Cloud Migration GCP to DigitalOcean, server to cloud, VM to container, cloud-to-cloud migration, database migration, application deployment migration, and infrastructure modernization. How I work: I focus on practical, reliable infrastructure — not overcomplicated setups. I investigate the real issue, explain what is happening clearly, fix it properly, and document the work so your team can continue confidently after the project is complete. If your GCP, AWS, Kubernetes, Terraform, CI/CD, Linux, or cloud infrastructure is unstable, expensive, or difficult to manage, send me a message with what you are trying to fix. I’ll tell you what I would check first and how I can help. Keywords / Relevant Skills: DevOps Engineer, Cloud Engineer, GCP Engineer, Google Cloud Engineer, AWS Engineer, AWS DevOps Engineer, AWS Cloud Engineer, Site Reliability Engineer, SRE, Platform Engineer, Kubernetes Engineer, Terraform Engineer, CI/CD Engineer, Infrastructure Engineer, Cloud Architect, Automation Engineer, Cloud Migration, Cloud Cost Optimization, GCP Cost Optimization, AWS Cost Optimization, Cloud Security, Linux, Docker, Kubernetes, GKE, EKS, Terraform, Ansible, Jenkins, GitHub Actions, Bitbucket Pipelines, Cloud Build, Azure DevOps, Helm, Prometheus, Grafana, CloudWatch, Monitoring, Infrastructure as Code, IaC, High Availability, Disaster Recovery, Security Hardening, DevSecOps.

Passionate about challenges and innovation! I'm a 25-year-old developer, holding a technical degree in Internet Computing from IFPE and currently pursuing a technology degree. AWS Certified, I'm working as SRE, with experience in Cloud Computing (especially AWS), process automation, DevOps, and observability. As a technical leader, I have hands-on experience with Node.js, Docker, Kubernetes, and Agile methodologies. I'm always looking for ways to improve systems and processes, driving efficiency and scalability in digital products. I write technical articles on my blog: liragui.github.io

🌟 18+ Years of Experience | Fortune 200+ Clients 🏆 Certified: Red Hat, AWS, Azure, VMware, Kubernetes (CKA), TOGAF I bridge the gap between high-level executive strategy and deep-technical execution. With nearly two decades of experience driving digital transformations, I specialize in architecting, building, and securing scalable enterprise platforms. I don't just design architectures; I build the AI-driven infrastructure, orchestrate the containerized deployments, and ensure autonomous reliability. Whether you need a Fractional CTO to guide your strategy, or a hands-on Senior SRE/DevOps engineer to modernize your platform engineering, I deliver solutions that optimize ROI and operational efficiency. 🚀 Core Areas of Expertise: ------ 1. Enterprise & Solutions Architecture (Fractional CTO): • Leading large-scale digital transformations, enterprise modernization initiatives, and complex cloud migration programs. • Designing AI-native platforms, Agentic AI systems, enterprise RAG architectures, multi-agent workflows, and LLM-powered business solutions. • Architecting microservices ecosystems, event-driven systems, robust APIs, and multi-tenant SaaS platforms for high-growth organizations. • Building scalable cloud, data, and AI infrastructure across hybrid, multi-cloud, and on-premises environments. • Bridging business strategy and technology execution for executives, stakeholders, and engineering teams while managing multi-million-dollar technology portfolios. • Driving platform reliability, security, governance, compliance, and operational excellence across enterprise-scale environments. ------ 2. AI Engineering, Agentic AI & AI Orchestration Architecture • AI Engineering & GenAI Platforms: Prompt Engineering, RAG Architecture, Fine-Tuning, LLM Integration (OpenAI, Hugging Face, Llama, Mistral), AI-Powered Enterprise Applications. • Agentic AI Engineering: Autonomous AI Agents, Multi-Agent Systems, Tool Calling, Function Execution, AI Workflows, Memory Management, Planning & Reasoning Architectures, Human-in-the-Loop Systems. • AI Orchestration Architecture: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, Workflow Orchestration, Event-Driven AI Systems, Agent Coordination and Governance. • LLMOps, MLOps & AI Operations: MLflow, Kubeflow, Ray, Model Registry, CI/CD for AI Systems, Model Monitoring, Evaluation Frameworks, Inference Optimization (vLLM, TensorRT). • Vector Search & Knowledge Systems: pgvector, OpenSearch, Milvus, Weaviate, Knowledge Graphs, Semantic Search, Enterprise Retrieval Systems. • Enterprise AI Infrastructure: Kubernetes, Docker, GPU Workloads, On-Prem AI Deployments, Hybrid Cloud AI Platforms, Secure RAG, AI Governance, Responsible AI. ------ 3. Platform Engineering, Cloud Infrastructure & Reliability Architecture • Platform Engineering & Cloud Architecture: Design and operation of enterprise platforms across AWS, Azure, GCP, OCI, Bare Metal, and Hybrid Cloud environments. • Containerization & Orchestration: Kubernetes, Docker, Helm, OpenShift, Cluster Operations, Multi-Cluster Management, and Cloud-Native Platform Engineering. • DevOps, GitOps & Infrastructure Automation: Terraform, Ansible, GitOps, CI/CD Pipelines (GitLab, Jenkins, GitHub Actions), Infrastructure as Code, and Automated Delivery Platforms. • Site Reliability Engineering (SRE) & Observability: OpenTelemetry, Prometheus, Grafana, SigNoz, ELK Stack, Distributed Tracing, Performance Engineering, Capacity Planning, and Self-Healing Architectures. • Network & Security Architecture: Zero-Trust Security, Firewall Design, VPN Technologies (WireGuard, OpenVPN), Network Segmentation, DNS Security, Email Security, Identity & Access Management. • Enterprise Infrastructure & Data Platforms: Linux/Windows Server Engineering, High Availability Systems, PostgreSQL, MongoDB, Redis, Advanced Caching Architectures, Database Performance and Scalability. ------ 💡 Why Partner With Me? ✅ Proven Track Record: 100+ successful enterprise projects with 100% client satisfaction. ✅ Seamless Communication: Proactive, professional, and clear documentation - no guesswork. ✅ Modern Standards: Heavy reliance on the latest development patterns, Policy-as-Code, and secure architectural frameworks. Let’s collaborate to modernize your infrastructure, integrate cutting-edge AI, and scale your platform with reliable, secure, and observable solutions. 📩 Send me a message today to discuss your project's architecture!

I'm an experienced and certified DevOps and Site Reliability Engineer with 10+ years working with various cloud-based projects and managing cloud infrastructure, CI/CD pipelines, building scalable and highly available systems. Formerly a software engineer (more than 15 years in total) with comprehensive experience building distributed systems with Java/Python/Golang/Web Application/DevOps/Cloud tech stacks and infrastructure. I have plenty of experience working with Cloud Infrastructure, Infrastructure as Code, Kubernetes/Docker/Compose/ECS, CI/CD and Automation, Configuration Management, Monitoring & Logging, and Security/DevSecOps. I also earned Certified DevOps Engineer - Professional level from AWS.

I help growing AI teams and SaaS companies fix AWS issues that slow releases, waste cloud budget, and put production at risk. Best fit for teams that need senior DevOps support for a launch, migration, infrastructure stabilization, AWS backend improvement, backend AWS architecture, or ongoing production ownership. I can support your team as an AWS DevOps Engineer, devops engineer, cloud engineer, aws architect, and senior delivery owner across Amazon Web Services, kubernetes, ci/cd, github actions, gitlab, Git, AWS Terraform, AWS Kubernetes, Azure DevOps, GCP DevOps, and terraform-based infrastructure. I don't just "run DevOps". Being Solution Oriented, I find the 20% of infrastructure issues causing 80% of failures and overspending: unstable pipelines, slow builds, noisy deployments, mis-sized compute, always-on non-prod environments, missing alerts, weak access controls, unsafe infrastructure changes, backend bottlenecks, full stack developer handoff issues, and weak collaboration between application and infrastructure teams. You get a clear action plan, quick wins in the first days, and production-safe improvements shipped via Terraform, AWS Terraform, CI/CD, ci cd pipelines, rollback-ready delivery, and practical DevOps Engineer execution using AWS Kubernetes, Microsoft Azure, azure data factory and Google Cloud Platform. What you get from a cloud infrastructure optimization engagement: ✅ 5x faster releases via stable CI/CD, ci cd workflows, and AWS Terraform driven delivery ✅ Up to 40% AWS cost reduction by eliminating waste and rightsizing resources ✅ Safer AWS migrations with minimal downtime and rollback plans ✅ Scalable, production-ready cloud infrastructure for growing SaaS and AI products utilizing AWS Kubernetes ✅ 99.9% uptime mindset: monitoring, backups, health checks, and safe rollouts across platforms ✅ Better AWS backend stability for backend, backend AWS, and API-driven platforms ⚙️ How I work as an AWS DevOps Engineer: 1️⃣ Discovery & Assessment: analyze your current Amazon Web Services, Linux servers, backend, kubernetes, AWS ECS, AWS Lambda, AWS EKS, EKS, Amazon EKS, GitLab, GitHub Actions, AWS Terraform, AWS Kubernetes, and deployment pain points 2️⃣ Plan: define clear scope, milestones, risks, and the fastest first win across your infrastructure 3️⃣ Implement: build and automate with AWS DevOps Engineer best practices, DevOps Engineer delivery standards, cloud engineer ownership, and clean documentation 4️⃣ Verify + handover: release runbook, rollback path tested, monitoring validated, and short documentation for your team I mainly work with AWS, but I can also support mixed-cloud teams where Microsoft Azure pipelines, Azure Terraform, Azure Cloud Engineer workflows, Azure infrastructure, Google Cloud Platform, AWS VMware, or migration planning are part of the environment. My expertise covers integrating AWS Terraform and AWS Kubernetes into multi-cloud setups. Real examples: Non-Production Cloud Cost Reduction (~30%) Problem: Dev and test environments were running 24/7, burning budget overnight with no business value. 🎯 Result: Reduced non-production AWS spend by ~30% through AWS DevOps Engineer cost review, rightsizing, and automated start/stop scheduling with zero production impact. CI/CD for AWS Lambda (Python/Node.js) & Web Apps Built 30+ pipelines as an AWS DevOps Engineer for AWS Lambda build and deploy workflows with unit tests and security gates, integrating them with Jenkins, Azure DevOps and GCP DevOps workflows. 🎯 Result: New AWS Lambda services, as well as JavaScript, React, WordPress, Laravel and MySQL backend stacks, can be provisioned from a template in minutes with consistent standards. AWS Terraform + runbooks Built AWS infrastructure as IaC with terraform modules, safe plan/apply workflows, AWS Kubernetes clusters, Ansible configuration, and devops bash automation. 🎯 Result: Performance environments provisioned in ~10 minutes to reduce AWS spend. Dagster Cloud Hybrid Agent on AWS ECS As a Senior DevOps Engineer, I built a Docker image and ci cd pipeline with GitHub Actions to deploy an agent into a client AWS account. 🎯 Result: Self-serve deployments and automated dataflow runs. IBM Cloud to AWS migration Designed architecture as aws architect, AWS DevOps Engineer, and cloud engineer. Rebuilt with kubernetes, AWS EKS, EKS, Amazon EKS, and Terraform. 🎯 Result: Production-ready foundation using AWS Kubernetes. Redshift cross-account migration Migrated cluster as devops engineer with data engineer handoff support. 🎯 Result: Reliable recovery runbook for faster response. Additional environments supported: Azure DevOps pipelines, Azure Terraform, Azure Cloud Engineer support, GCP DevOps, AWS VMware, AWS Terraform, full stack developer issues, backend stabilization, backend AWS architecture, and data engineer infrastructure. ☎️ Message me a short description of your current pain for fast Senior AWS DevOps Engineer support.

I help businesses build, automate, deploy, and scale AI-powered applications, cloud infrastructure, and intelligent automation solutions. With a strong background in DevOps, Cloud Engineering, Site Reliability Engineering (SRE), and AI Development, I specialize in creating production-ready systems that are scalable, secure, and highly available. I combine modern AI technologies with robust cloud infrastructure to deliver solutions that improve efficiency, reduce operational overhead, and accelerate business growth. My expertise spans the complete lifecycle of AI and cloud solutions—from AI agent development and LLM integration to infrastructure automation, CI/CD implementation, Kubernetes orchestration, and cloud-native architecture. ### AI Engineering & Automation ✅ AI Agent Development (OpenAI, Claude, Gemini, LangChain, CrewAI) ✅ LLM Applications, RAG Systems, AI Chatbots, and Copilots ✅ AI Workflow Automation using n8n ✅ AI Model Training, Fine-Tuning, Evaluation, and Deployment ✅ Multi-Agent Systems and Enterprise AI Integrations ✅ Generative AI Applications and Intelligent Assistants ✅ Speech-to-Text, Text-to-Speech, and AI-Powered Automation ✅ AI Monitoring, Optimization, and Production Deployment ### DevOps, Cloud & SRE ✅ AWS, Azure, and Cloud Infrastructure Management ✅ Kubernetes (EKS, AKS), Docker, Helm, and Container Orchestration ✅ CI/CD Pipelines using Jenkins, GitHub Actions, GitLab CI, and Azure DevOps ✅ Infrastructure as Code (Terraform, CloudFormation, AWS CDK) ✅ Linux Administration and Server Performance Optimization ✅ Monitoring and Observability using Prometheus, Grafana, ELK Stack ✅ High Availability, Auto Scaling, Disaster Recovery, and Reliability Engineering ✅ Security, Networking, VPNs, Load Balancers, WAF, and Cloud Governance ### Technical Expertise # AI & Generative AI AI Agent Development Large Language Models (LLMs) OpenAI API, Claude API, Gemini API LangChain, LangGraph, CrewAI Retrieval-Augmented Generation (RAG) AI Chatbots & Copilots Prompt Engineering AI Workflow Automation (n8n) AI Model Training & Fine-Tuning Model Evaluation & Optimization Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS) AI API Integration Multi-Agent Systems Speech-to-Text & Text-to-Speech Solutions Generative AI Applications AI Deployment & MLOps #Cloud Platforms AWS (EC2, ECS, EKS, Lambda, S3, CloudFront, Route53, RDS, DynamoDB, VPC, Auto Scaling, Load Balancers) Azure (Azure DevOps, AKS, Virtual Machines, Application Gateway, WAF, Blob Storage, API Management) #Containerization & Orchestration Docker, Kubernetes, Helm, EKS, AKS, Minikube #Infrastructure as Code Terraform, CloudFormation, AWS CDK, Ansible # Programming & Automation Python Bash Shell Scripting PowerShell JavaScript (ES6+) TypeScript Node.js Next.js Express.js Flask Django FastAPI .NET / ASP.NET Core C# Java Spring Boot REST APIs GraphQL Webhooks JSON / YAML SQL PostgreSQL MySQL MongoDB Redis Git Linux Automation Infrastructure Automation API Integration Workflow Automation (n8n) CI/CD Automation AI Workflow Orchestration MCP (Model Context Protocol) LangChain LangGraph CrewAI Agentic AI Development RAG Pipeline Development Vector Database Integration ETL & Data Processing Automation # AI & ML Development OpenAI API Claude API Gemini API Hugging Face Transformers PyTorch TensorFlow Scikit-learn Fine-Tuning LLMs Model Training Model Evaluation Prompt Engineering Embedding Models AI Agent Development Multi-Agent Systems MLOps LLM Deployment AI Observability Speech-to-Text (STT) Text-to-Speech (TTS) #Monitoring & Observability Prometheus, Grafana, ELK Stack, Centralized Logging #Version Control & Collaboration Git, GitHub, GitLab, Bitbucket, Azure Repos, SVN #Web & Application Servers Nginx, Apache, Tomcat, IIS ### Email Infrastructure Expertise ✅ MailWizz Deployment and Management ✅ KumoMTA Configuration and Optimization ✅ SMTP Infrastructure Setup ✅ Email Deliverability and Sending Architecture ✅ Dedicated IP and Domain Configuration ### What I Deliver • AI Agents and Enterprise Automation Solutions • Production-Ready Cloud Infrastructure • Scalable Kubernetes Platforms • End-to-End DevOps Implementations • CI/CD and Release Automation • AI-Powered Business Workflows • Secure, Reliable, and Highly Available Systems Whether you need an AI-powered chatbot, a multi-agent workflow, cloud migration, Kubernetes deployment, infrastructure automation, DevOps consulting, or a complete AI + Cloud solution, I can help transform your requirements into scalable production systems.

Myself Harshal Jethwa – a passionate and detail-oriented DevOps & Site Reliability Engineer (SRE) with a strong foundation in Cloud Computing and a solid academic background in Information Technology and Computer Engineering. 🚀 With certifications from AWS (Cloud Practitioner) and Microsoft (Azure Fundamentals), I bring hands-on experience in building, automating, and managing scalable, secure, and high-availability systems. I’m actively exploring and working with multi-cloud platforms, DevOps pipelines, infrastructure as code (Terraform, Ansible), Kubernetes, and cloud-native monitoring tools like Prometheus and Grafana. 💡 What sets me apart is not just my technical proficiency—but also my passion for learning, mentoring, and sharing knowledge. I love simplifying complex cloud concepts and guiding others on their cloud journey, which has made me a valued mentor in various tech communities. 🎯 I'm currently open to freelance/contract DevOps and Cloud Engineering projects, where I can bring value by automating infrastructure, improving system reliability, optimizing cloud costs, and delivering fast, secure CI/CD solutions. 🧠 Tech Stack & Interests: AWS | Azure | GCP (Learning) Docker | Kubernetes | CI/CD (GitHub Actions, Jenkins) Terraform | Ansible | Linux | Bash | Python SRE Practices | Cloud Monitoring | Web Development (Frontend/Backend Basics) 💬 Let’s connect if you're looking for someone who’s not only skilled but also enthusiastic, reliable, and committed to delivering results. I bring with me not just code—but clarity, collaboration, and cloud-first thinking.