I'm a Kubernetes and Rancher expert passionate about designing, building, and implementing scalable solutions for organizations of all sizes. With extensive experience in infrastructure and network analysis and design, I can provide customized Kubernetes and Rancher solutions that meet my client's specific needs. My expertise includes designing and implementing CI/CD pipelines, creating custom resources, and integrating APIs with Kubernetes and Rancher. I have experience working with various Kubernetes distributions, including RancherOS, k3s, RKE1/2, and Longhorn, and I am always excited to learn about new technologies and tools that can improve my work. In addition to my hands-on experience, I hold several certifications demonstrating my field expertise. I'm a SUSE Certified Administrator in SUSE Rancher v2.5, a Certified Kubernetes Administrator (CKA), a Certified Kubernetes Application Developer (CKAD), and a Certified Kubernetes Security Specialist (CKS). When working with clients, my main goal is to help them achieve their desired outcomes and exceed their expectations. I take a collaborative and consultative approach, listening carefully to my client's needs and providing expert guidance and support throughout the process. If you're looking for a skilled Kubernetes and Rancher expert to help you build a reliable, scalable infrastructure, please don't hesitate to get in touch. I'm always happy to chat and provide more information about my experience and approach.

Resilient, observable infrastructure designed to scale with your business. Six years of GCP, Kubernetes, and SRE expertise reducing downtime, cutting cloud costs, and eliminating deployment risk. ● 6+ years of hands-on experience as a DevOps & Cloud Engineer specializing in Google Cloud Platform (GCP), Kubernetes orchestration, and SRE practices. ● Expertise in Infrastructure as Code (IaC) using Terraform and Ansible for automated, scalable, and resilient cloud architectures. ● Strong proficiency in Kubernetes (GKE & EKS), including cluster optimization, autoscaling, service mesh, and workload management. ● Advanced CI/CD automation skills using Jenkins, GitHub Actions, and GitLab CI for zero-downtime deployments. ● Deep Linux systems expertise with advanced shell scripting (Bash) and Python for system hardening and performance optimization. ● Specialized in Observability using Prometheus, Grafana, ELK, and Stackdriver to reduce incidents and monitor SLAs. ● Proven track record in designing secure, HIPAA-compliant, and multi-tenant SaaS infrastructures. KEY RESPONSIBILITIES 1. Cloud Architecture & Infrastructure as Code (IaC) ● Architected and deployed scalable GCP environments using Compute Engine, GKE, Cloud Storage, and VPC. ● Automated end-to-end infrastructure provisioning using Terraform modules for VPC, Cloud NAT, IAM, and Cloud SQL. ● Implemented configuration management via Ansible to ensure environment standardization and reduce operational overhead. 2. Kubernetes Orchestration & Containerization ● Designed and managed GKE-based microservices with node pool optimization and secure service communication. ● Hardened Kubernetes security using RBAC policies, network policies, and private clusters. ● Streamlined application packaging and deployment using Docker and Helm-based charts. 3. CI/CD Pipeline Engineering ● Engineered robust CI/CD pipelines in GitHub Actions, Jenkins, and GitLab CI for container builds and automated testing. ● Implemented advanced deployment strategies, including Canary, Blue-Green, and Rolling updates, improving system uptime by 35%. ● Integrated automated rollback mechanisms and artifact versioning to ensure delivery pipeline reliability. 4. SRE, Monitoring & Observability ● Built comprehensive observability frameworks using Prometheus, Grafana, and Stackdriver for real-time metrics and alerting. ● Integrated SLO-based alerting and error budgets into incident workflows to improve service reliability. ● Optimized system performance by automating failover, pod disruption budgets, and resilient service deployments. 5. Security, Compliance & Networking ● Ensured data protection and compliance (including HIPAA) using KMS encryption, IAM least-privilege, and audit logging. ● Secured cloud networks using VPC Service Controls, ingress/egress firewalls, and IAM conditions. ● Managed identity and access through IAM and RBAC to enforce strict tenant isolation in multi-tenant SaaS platforms. 6. Event-Driven & Serverless Solutions ● Designed high-performance event-driven workflows using Pub/Sub, Cloud Functions, and EventArc, achieving up to 60% latency reduction. ● Integrated Cloud Run for serverless execution and cost-effective scaling of background processes.

🌟 DevOps & Solution Eng. Lead | AWS | Terraform | Gitlab | Kubernetes | Linux 🚀🌍 Passionate about technology, I'm a DevOps and Solution Engineering Lead with expertise in AWS, Terraform, Gitlab, Kubernetes, and Linux. 🖥️💡 With a keen eye for system design and a love for FinTech, I thrive in dynamic environments where I can drive product development and innovation. 📈💼 As an avid traveler and gadget freak, I constantly seek new adventures and embrace the latest technologies. From exploring the stunning landscapes of 🇧🇩 Bangladesh to the bustling cities of 🇦🇪 UAE, 🇸🇬 Singapore, 🇲🇾 Malaysia, and 🇮🇪 India, I find inspiration in the diversity of cultures and experiences. ✈️🌏 Join me on this exciting journey of entrepreneurship as we create meaningful solutions and push the boundaries of what's possible in the world of technology! 🚀💪 #DevOps #AWS #Terraform #Gitlab #Kubernetes #Linux #FinTech #MERNStack #CMS #CI/CD #ProductDevelopment #Entrepreneurship #TravelEnthusiast #GadgetFreak

Your infrastructure should ship product, not slow it down. I'm Ehtisham, founder of ePrecisio Technologies (US LLC). CKA & CKAD certified. 8 years building production-grade Kubernetes, MLOps pipelines, and cloud platforms for funded startups and enterprise teams across the US, EU, and MENA. ━━━━━━━━━━━━━━━━━━━━ 🚀 WHAT I'VE SHIPPED ━━━━━━━━━━━━━━━━━━━━ Stack8s (UK, Funded) Full Kubernetes platform. 15+ cloud providers unified, 100+ component marketplace, GPU compute. Live in production. Aceso (Norway) ML infrastructure. Kubeflow, multi-cloud Kubernetes, Istio. GDPR-compliant. 5+ years running. Calibras (Denmark) 40% cloud cost reduction (FinOps). Multi-cloud Terraform, full CI/CD overhaul. 99.9% SLA delivered. Imperial College London On-prem Kubernetes research cluster. Bare-metal, GPU node management. 100% uptime over 2 years. Tanweel (Saudi Arabia) Fintech-grade DevOps. Hardened Kubernetes, IaC, audit-ready (SAMA compliance). TeamCare Dental (US) HIPAA-aligned multi-tenant SaaS. AWS, secure architecture, compliance-ready. FindSocial Agentic data pipelines. 1M+ leads processed. Python, FastAPI, PostgreSQL, AWS. Songplace (Netherlands) · 8-Year Partnership Full music tech platform. React, FastAPI, AWS, Stripe, Spotify API, LLM recommendations. ━━━━━━━━━━━━━━━━━━━━ ⚙️ WHAT I WORK WITH ━━━━━━━━━━━━━━━━━━━━ Platform Engineering · SRE & Observability · FinOps Kubernetes (EKS, AKS, GKE, K3s) · Terraform · ArgoCD · GitHub Actions Kubeflow · MLflow · Prometheus · Grafana · Istio · HashiCorp Vault AWS · Azure · GCP · FastAPI · Docker GDPR · HIPAA · SOC 2 · SAMA ━━━━━━━━━━━━━━━━━━━━ 📋 HOW I ENGAGE ━━━━━━━━━━━━━━━━━━━━ ✔ Fixed 2-week sprint to start. No retainer required. ✔ You own 100% of the code from day one. ✔ Free 30-min infrastructure audit included. Ready to fix your infrastructure? Message me to book your free audit.

I run a DevOps agency helping SaaS companies and IT businesses scale faster by providing senior DevOps engineers who optimize cloud infrastructure, accelerate deployments, and ensure production stability at scale. Our DevOps team partners with engineering leaders who need reliable, secure, and cost-efficient cloud systems — without hiring and managing an in-house team. Our engineers specialize in designing, building, and maintaining secure and scalable cloud environments across AWS, Microsoft Azure, and Google Cloud Platform (GCP). Whether you're starting from scratch or managing a complex multi-cloud setup, we architect AWS-native and cross-cloud solutions that are resilient and production-ready. → Cloud Infrastructure & Migration We handle end-to-end cloud infrastructure design and cloud migration projects — moving legacy systems to AWS, Azure, or GCP with zero disruption to your business. Our DevOps engineers assess your existing architecture, build a migration roadmap, and execute the migration while maintaining security, performance, and compliance throughout every phase. Whether it's a lift-and-shift to AWS or a full re-architecture on GCP, we own the migration end to end. → DevOps & CI/CD Automation We design and implement robust CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, and ArgoCD — reducing release cycles from weeks to hours. Our GitOps-based CI/CD delivery model ensures consistent, auditable deployments with full automation of build, test, and deploy workflows, eliminating manual processes and human error across every cloud environment. Every DevOps engagement includes CI/CD as a foundation, not an afterthought. → Infrastructure as Code (IaC) & Configuration Management We manage all cloud infrastructure through Terraform and Ansible, ensuring predictable, repeatable, and version-controlled IaC environments. Terraform modules are written to be reusable across AWS, Azure, and GCP — making Terraform the single source of truth for your infrastructure. IaC practices allow your team to scale confidently and roll back safely when needed, with Terraform state managed securely in remote backends. → Kubernetes & Container Orchestration Our DevOps engineers build and operate containerized systems using Docker and Kubernetes, supporting high-load, distributed applications. From Kubernetes cluster setup on AWS EKS, Azure AKS, or GCP GKE, and Helm chart management to Docker-based autoscaling and multi-tenant workloads — we make Kubernetes work reliably in production. Docker image optimization and Kubernetes resource tuning are part of every engagement. → Security & Compliance (DevSecOps) Security is embedded at every layer of our DevOps work. We implement cloud security best practices across AWS, Azure, and GCP, integrate security scanning into CI/CD pipelines, manage secrets with HashiCorp Vault, and support security compliance automation for SOC 2, HIPAA, and PCI-DSS requirements. AWS security configurations — IAM, VPC, Security Groups, GuardDuty — are applied from day one of every migration or infrastructure project. → Monitoring, Observability & Incident Response We set up full-stack monitoring and observability using Prometheus, Grafana, Datadog, and the ELK stack — giving your team complete visibility into cloud infrastructure health. Proactive monitoring and observability practices catch production incidents before they impact users, reducing downtime and keeping your Kubernetes and Docker workloads stable. Every AWS, Azure, and GCP environment we deliver includes monitoring as a core deliverable, not an optional add-on. 📌 Core Expertise - Cloud Platforms: AWS | Microsoft Azure | Google Cloud Platform (GCP) - DevOps & CI/CD: GitHub Actions | GitLab CI | Jenkins | ArgoCD - Containers & Orchestration: Docker | Kubernetes | Helm - Infrastructure as Code (IaC): Terraform | Ansible - Monitoring & Observability: Prometheus | Grafana | Datadog | ELK Stack - Security: HashiCorp Vault | Security Scanning | Compliance Automation - Cloud Migration: Legacy-to-cloud | Multi-cloud | Lift-and-shift | Re-architecture 📌 Why clients choose us: ✅ Senior DevOps engineers with 10+ years of average hands-on AWS, Azure, and GCP production experience ✅ Full-cycle ownership — from cloud architecture and Terraform design to ongoing monitoring and support ✅ Proven track record in cloud migration, Kubernetes adoption, and CI/CD transformation ✅ Reduced deployment time, lower AWS and cloud infrastructure costs, and fewer production incidents ✅ Transparent communication, clear IaC and Terraform documentation, and fast response times

𝗦𝗲𝗻𝗶𝗼𝗿 𝗗𝗲𝘃𝗢𝗽𝘀 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 & 𝗖𝗹𝗼𝘂𝗱 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 | 𝗖𝗹𝗼𝘂𝗱-𝗡𝗮𝘁𝗶𝘃𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻, 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻, 𝗜𝗮𝗖, | 𝗔𝗪𝗦, 𝗚𝗖𝗣, 𝗔𝘇𝘂𝗿𝗲 | 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀, 𝗧𝗲𝗿𝗿𝗮𝗳𝗼𝗿𝗺, 𝗚𝗶𝘁𝗛𝘂𝗯 𝗔𝗰𝘁𝗶𝗼𝗻𝘀, 𝗔𝗻𝘀𝗶𝗯𝗹𝗲 | 𝗖𝗜/𝗖𝗗 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀, 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 & 𝗦𝗶𝘁𝗲 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 (𝟭𝟮+ 𝘆𝗿𝘀 𝗘𝘅𝗽) I help companies design, automate, and scale reliable cloud platforms that ship software faster and operate efficiently. With 12+ years in DevSecOps & Cloud Engineering, I specialize in building secure, high-availability systems across AWS, Azure, and GCP, empowering teams to deliver with confidence and speed. Alongside traditional DevOps excellence, I architect modern AI-driven platforms powering LLM applications, vector DB systems, GPU workloads, and automated workflows. From Kubernetes-based AI clusters to n8n and Airflow automation pipelines, I ensure AI products move smoothly from prototype to scalable production. ✅ 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗜’𝘃𝗲 𝘄𝗼𝗿𝗸𝗲𝗱 𝘄𝗶𝘁𝗵 𝗵𝗮𝘃𝗲: 👉 Reduced deployment times by up to 70% through automated CI/CD pipelines. 👉 Optimized cloud spend by 25–40% with better architecture and monitoring. 👉 Achieved 99.99% uptime with resilient Kubernetes clusters and HA systems. ⚙️ 𝗦𝗲𝗿𝘃𝗲𝗿 𝗔𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 👉 Linux Server Administration (Ubuntu, CentOS, RHEL) 👉 Networking & Security (VPC, VPNs, DNS, SSL, Firewalls, Load Balancers) 👉 System Hardening & Access Control (IAM, RBAC, MFA) 👉 Database & Caching Systems (MySQL, PostgreSQL, MongoDB, Redis, Memcached) 👉 Scripting & Automation (Bash, Python) 👉 Virtualization & Compute (VMware, EC2, Compute Engine, Azure VMs) 🛠️ 𝗗𝗲𝘃𝗦𝗲𝗰𝗢𝗽𝘀 | 𝗗𝗲𝘃𝗢𝗽𝘀 & 𝗖𝗹𝗼𝘂𝗱 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 👉 Cloud Platforms: AWS, Azure, GCP, DigitalOcean, Alibaba Cloud 👉 Containerization & Orchestration: Docker, Kubernetes, Helm, OpenShift 👉 Infrastructure as Code: Terraform, Ansible, CloudFormation, Puppet 👉 CI/CD Pipelines: Jenkins, GitHub Actions, GitLab CI, Bitbucket Pipelines 👉 Monitoring & Observability: Prometheus, Grafana, ELK, Datadog, New Relic 👉 Secret Management & Compliance: HashiCorp Vault, SOC2 / ISO27001 best practices 👉 Cost Optimization & FinOps Practices 🤖 𝗔𝗜 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 & 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 👉 AI & MLOps Platforms: SageMaker, Vertex AI, Hugging Face, Kubeflow, MLflow 👉 Vector Databases: Pinecone, Qdrant, Redis-Search / Redis-Stack 👉 LLM & GPU Workloads: Distributed model hosting, autoscaling, inference optimization 👉 AI-Ready Kubernetes: GPU nodes, inference services, model rollout workflows 👉 Workflow Automation: n8n, Airflow, event-driven pipelines 👉 Serverless AI & Edge Deployments: Lambda, Cloud Run, Vercel Edge Functions 👉 API & Model Integration: LangChain, OpenAI stack, secure model gateways 🎯 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 I build secure, scalable, and automated cloud and AI-ready infrastructure that helps teams ship faster, reduce costs, and operate with confidence. My focus is DevSecOps-driven platforms, efficient CI/CD delivery, and reliable Kubernetes environments built for real-world scale. I also deploy modern AI infrastructure, including GPU-based model serving, vector databases, and automation workflows with n8n and Airflow, taking AI products from prototype to production smoothly. The result: systems that are resilient, cost-efficient, disaster-ready, and built to grow with your business. 📌 𝗪𝗵𝘆 𝗛𝗶𝗿𝗲 𝗠𝗲? If you need a hands-on DevOps partner who can design, automate, and optimize your infrastructure while ensuring speed, security, and scalability - I can help. I don’t just build systems; I make sure they deliver business value through efficiency, resilience, and reduced costs. 𝗟𝗲𝘁’𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝗮𝗻𝗱 𝗱𝗶𝘀𝗰𝘂𝘀𝘀 𝗵𝗼𝘄 𝗜 𝗰𝗮𝗻 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝘀𝘁𝗿𝗲𝗮𝗺𝗹𝗶𝗻𝗲 𝘆𝗼𝘂𝗿 𝗶𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁𝘀, 𝗮𝗻𝗱 𝗺𝗮𝘅𝗶𝗺𝗶𝘇𝗲 𝗥𝗢𝗜 𝗼𝗻 𝘆𝗼𝘂𝗿 𝗰𝗹𝗼𝘂𝗱 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁𝘀. 👉 𝗛𝗮𝘀𝗵𝘁𝗮𝗴𝘀 𝘁𝗼 𝗳𝗶𝗻𝗱 𝗺𝗲 #DevOps #DevSecOps #SRE #CloudArchitect #AWS #Azure #GCP #Kubernetes #Docker #Terraform #Ansible #GitOps #CICD #Jenkins #GitHubActions #GitLabCI #ArgoCD #Helm #InfrastructureAsCode #PlatformEngineering #CloudSecurity #Monitoring #Prometheus #Grafana #ELK #Datadog #Serverless #Automation #n8n #Airflow #WorkflowAutomation #MLOps #AIInfrastructure #LLMDeployment #GPUCloud #SageMaker #VertexAI #HuggingFace #LangChain #VectorDB #Pinecone #Qdrant #Redis

I have over 7+ years experience in Software Engineering and DevOps. I am a Certified Kubernetes Administrator, Certified by The Linux Foundation. Currently, the industry is unsure what name to give the responsibilities that comes with a true DevOps Engineer, but I am able to fill all of them DevOps, DevSecOps, SRE (System Reliability Engineer), and Automation Engineer. I prefer to work within AWS (Amazon Web Services) or GCP (Google Cloud Platform) for most of my DevOps tasks, as this is the way most companies are moving. Some of the tasks that I have done in this space are: - Help startups build initial infrastructure, with full automation - Migrate larger, existing companies to various cloud providers - Automate existing workflows and CI/CD pipelines - Consult on system architecture for efficiency and cost savings Tech stack that I have most experience - - Public Cloud: AWS, GCP - Private Cloud: OpenStack - DevOps daily stuff: CI/CD, Git workflow, Automation Test/Deployment with Gitlab, Jenkin - Logging and monitoring: ELK stack, Grafana, Prometheus - Virtualization: Vmware, KVM - Containerization: Docker, Kubernetes(self-hosted, EKS, GKE) - Database: SQL(Postgres, MySQL, MariaDB), NoSQL(MongoDB, Cassandra, Couchbase), Timeseries(Elasticsearch) - Networking infrastructure - Software lifecycle principal - Coding with: NodeJS, Python, Bash Shell

Here’s a clean, Upwork-ready rewrite you can paste into your profile. I kept it human, specific, and keyword-rich for search—while showcasing your 14+ years across cloud, DevOps, and automation. ✅ Cloud Architect & DevOps Engineer | AWS • GCP • Azure | Kubernetes • Terraform • CI/CD • DevSecOps I help companies design, secure, and automate cloud platforms that scale—from zero to production and beyond. With 14+ years across cloud engineering, DevOps architecture, and infrastructure automation, I’ve built end-to-end systems that start from a blank account and evolve into resilient, compliant, cost-efficient production environments. I work hands-on across AWS, GCP, and Azure; design robust networking (VPC/VNet, peering, VPN, Direct Connect/Interconnect, Transit); and automate everything with Terraform/Pulumi and modern CI/CD. Security and observability are baked in from day one. What I do Greenfield to Production: Ground-up cloud architecture, IaC, GitOps, and day-2 operations. Secure by Design: Network segmentation, least-privilege IAM, secrets, policy as code, and DevSecOps pipelines. Kubernetes at Scale: EKS/GKE/AKS design, cluster add-ons, multi-cluster/multi-region, HPA/VPA, autoscaling. High Throughput Systems: Architecting for millions of requests/second with caching, queues, and horizontal scale. Cost & Reliability: Right-sizing, spot strategy, autoscaling, SLOs, and disaster recovery runbooks. Recent impact (high level) Designed multi-region Kubernetes + GitOps platform to support spiky workloads with safe blue/green rollouts. Implemented full DevSecOps pipeline (SAST/DAST/Secrets/Dependency scanning) with policy gates and audit trails. Delivered VPC/VNet designs with private service access, egress controls, and zero-trust access patterns. Services Cloud Infrastructure ✔ Multi-cluster, multi-region VPC/VNet architectures with zonal resilience ✔ Security group / firewall / route audits ✔ Subnetting, routing, NAT/egress, private endpoints, WAF, IDS/IPS integration ✔ Connectivity: Direct Connect / Interconnect / ExpressRoute, IPSec VPN, Transit topologies, VPC peering ✔ AWS services: EKS, EC2, Lambda, RDS, Aurora, S3, CloudFront, ALB/NLB, Systems Manager, IAM DevOps & Automation ✔ Terraform (modules, workspaces, Terragrunt), Pulumi ✔ CloudFormation where required ✔ CI/CD: GitHub Actions, GitLab CI, Azure DevOps, Jenkins, CircleCI, TravisCI ✔ GitOps with Argo CD / Flux, progressive delivery (blue/green, canary) ✔ DevSecOps: SAST/DAST/Secrets/Dependency scanning, SBOMs, policy as code (OPA/Conftest), image signing Kubernetes & Containers ✔ Managed K8s: EKS / GKE / AKS, plus K3s for edge/lab ✔ Helm chart authoring & lifecycle, Kustomize overlays, ApplicationSets ✔ Dockerization of .NET, Java, PHP, Go, Python apps; multi-stage builds; security baselines ✔ Observability: Prometheus/Grafana, logging, tracing; alerts tied to SLOs ✔ Autoscaling: HPA/VPA/Cluster Autoscaler; spot/priority classes; node pools & taints/tolerations How I work Architecture first, automation always: Clear diagrams, ADRs, and repeatable IaC. Security & compliance built-in: Least-privilege IAM, encryption, image/signature policies, supply-chain controls. Operability: Dashboards, alerting, runbooks, and DR/backup strategies you can actually use. Transparent delivery: Milestone plans, PR-driven changes, and documentation for easy handover. Tech stack (abridged) Cloud: AWS, GCP, Azure IaC: Terraform, Terragrunt, Pulumi, CloudFormation CI/CD: GitHub Actions, GitLab, Azure DevOps, Jenkins, CircleCI, TravisCI Kubernetes: EKS, GKE, AKS, K3s • Helm, Kustomize, Argo CD/Flux • Ingress/WAF/Cert-Manager Security: IAM, KMS/Envelope, OPA/Conftest, SAST/DAST, image signing, SBOMs Data & Runtime: RDS/Aurora, S3/GCS/Blob, Redis, MQ, Lambda/Functions, container registries Observability: Prometheus, Grafana, Loki/ELK, OpenTelemetry Engagement options Architecture & Implementation: Design → IaC → CI/CD → secure rollout. Platform Hardening:Security review, IAM/VPC hardening, cost/risk reduction. Kubernetes Enablement:Cluster build-out, add-ons, GitOps, SRE baselines. Migrations: Lift-and-shift with refactoring for scale, reliability, and cost. Let’s talk If you need a secure, automated cloud foundation—or want to level up what you already have—send a message with your goals and timelines. I’ll propose a practical plan with clear milestones and outcomes.

Most infrastructure engineers can set up a cluster. Few have deployed production AI stacks on top of one. I'm a CKA-certified Kubernetes engineer. I work with startups that need someone who can own infrastructure end-to-end from bare-metal cluster bootstrap to self-hosted LLM deployment and stay accountable when things break in production. Where I add value others don't: Self-hosted AI stacks in production: Ollama, Weaviate, vector DBs, RAG pipelines on K8s Multi-tenant Kubernetes architecture with namespace isolation, NetworkPolicies, RBAC Zero-trust networking with Netbird and Wireguard Security-aware pipelines: OWASP ZAP scanning, Vault, CIS hardening Full observability: Prometheus, Grafana, Loki, alerting, runbooks Core stack: Kubernetes · Docker · Terraform · GitHub Actions · GitLab CI · Jenkins · Prometheus · Grafana · AWS · Linux My clients describe me as someone who communicates clearly, solves problems fast, and doesn't disappear when things get hard. If you need infrastructure that holds under pressure, let's talk.

I architect production ML and AI/LLM platforms for enterprises and AI-native startups. My work spans the full system: model serving (self-hosted on Kubernetes or via OpenAI, Anthropic, and Bedrock APIs), MLOps and CI/CD, observability, and the governance posture that lets these systems hold up in regulated environments. A lot of engagements start with helping teams decide which workloads belong where, then building the platform to support them. *Background*: · 8+ years building ML platforms across AWS, GCP, and on-prem · Cloud Infrastructure Engineer at Royal Bank of Canada: hybrid AKS/Anthos migration of a critical API platform under bank change management · ML Infrastructure Developer at BorealisAI (RBC's AI research institute): SLURM on NVIDIA DGX, OpenShift CI/CD for ML pipelines · Through HADI Technology, recent client engagements include SkanAI (production ML infrastructure on Kubernetes), Joinable (self-hosted LLM serving), Fylo (graph RAG and neurosymbolic AI platform), and ZahraTrust (AI agent infrastructure) *Recent work*: · Self-hosted LLM serving on Kubernetes with vLLM and KubeAI (DeepSeek-R1, Llama 3); continuous batching, autoscaling, OpenAI-compatible API surface · Graph RAG and neurosymbolic extraction pipelines combining vector retrieval with ShEx-constrained schema validation for accuracy and traceability · Reusable MLOps platform components (MLflow, Argo CD, Terraform, Helm) so domain teams onboard new ML workloads in days · Cross-cloud ML pipelines on AWS and GCP with unified experiment tracking, artifact management, and gated promotion · Production observability for ML systems (Prometheus, Grafana, EFK) with alerting on latency, throughput, drift, and cost *Good fit if you're*: · Running LLMs in production and the infrastructure is becoming the bottleneck · Deciding between API, self-hosted, or hybrid for a given workload · Moving from ad-hoc ML deployments to a structured internal ML platform with proper lifecycle controls · In a regulated industry (banking, healthcare, government) and need infrastructure that holds up to compliance review *Stack*: vLLM, KubeAI, MLflow, Triton Inference Server, ONNX Runtime, Kubernetes, OpenShift, Terraform, Argo CD, Helm, Airflow, Prometheus, Grafana, Vault, AWS, GCP, SLURM I typically begin engagements with a 2-3 week architecture assessment, so we can scope the right system together before committing to a multi-month build.