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Are your deployments slow, breaking at the worst moments, or costing more than they should? Is your team spending hours on manual releases instead of shipping features? If your CI/CD pipelines are fragile, your Azure infrastructure is growing out of control, or your DevOps processes exist only on paper, you are dealing with a problem that will not fix itself. I am a DevOps Engineer and Azure Architect with 10+ years of experience helping product teams and growing companies build cloud infrastructure that actually works. Whether it is a startup scaling fast or an enterprise team drowning in legacy pipelines, I come in, assess the real state of things, and build systems that are stable, automated, and cost-efficient. My primary expertise is Microsoft Azure and Azure DevOps, end to end. That means everything from designing multi-stage Azure DevOps pipelines and managing releases without downtime, to setting up Azure DevOps RBAC, securing environments, and integrating Azure DevOps with Kubernetes clusters running on AKS. I have built Azure DevOps workflows for teams of 5 and teams of 150, and the approach scales both ways. Every Azure DevOps implementation I deliver is built around real business goals, not just tooling checkboxes. Beyond Azure DevOps, I work across the full infrastructure stack. I design Cloud Architecture using Terraform for Infrastructure as Code, manage containerized workloads with Kubernetes and Docker, and implement Deployment Automation that removes human error from the release process. For data-heavy projects, I build pipelines with Azure Data Factory to handle ETL, orchestration, and integration between services. For teams building decentralized or blockchain-integrated solutions, I have worked with Azure Blockchain Service as part of broader Microsoft Azure infrastructure setups, combining it with the same security and governance standards applied across all environments. As an Azure Architect, I cover Cloud Computing governance, cost optimization, and FinOps practices, so your Azure bill reflects actual usage, not waste. I apply the same structured thinking to Network Security, Linux and Windows Server environments, and multi-cloud setups when needed. When projects require Amazon Web Services, I bring the same DevOps standards to AWS, including AWS DevOps pipelines, CI/CD automation, and infrastructure managed through Terraform. I also work with Google Cloud Platform for teams running workloads across multiple providers. AI Automation is a growing part of what I do. As more teams start integrating AI into their products and workflows, I help them connect those AI components to production infrastructure properly, with reliable pipelines, automated testing, and deployment flows that treat AI workloads the same way as any other service. I also collaborate closely with full stack developer teams to improve release processes, deployment reliability, and infrastructure scalability, making sure the gap between development and operations is as small as possible. What clients usually need help with: ✔ Stabilizing Azure DevOps pipelines and deployment workflows ✔ Building scalable Kubernetes infrastructure ✔ Migrating legacy infrastructure to Microsoft Azure ✔ Reducing cloud costs and improving DevOps efficiency ✔ Designing secure Cloud Architecture for growing products ✔ Automating deployments with Terraform and CI/CD ✔ Improving monitoring, security, and infrastructure reliability ✔ Implementing AI Automation into existing delivery workflows The full technology range I work with includes: Azure DevOps, Microsoft Azure, Amazon Web Services, Google Cloud Platform, Kubernetes, Docker, Terraform, Ansible, CI/CD, Git, SQL, Python, Linux, Windows Server, Azure Data Factory, Azure Blockchain Service, Cloud Architecture, Deployment Automation, Network Security, and more. Certifications: ✅ 8x Microsoft Azure Certified ✅ Kubernetes Certified ✅ Terraform Certified If your infrastructure needs structure, your pipelines need reliability, or your cloud costs are climbing without clear control, send me a message here on Upwork. Describe the situation and I will come back with a clear breakdown and concrete next steps.

Platform/DevOps Engineer with a decade of hands-on experience optimizing delivery pipelines, automating infrastructure, and deploying containerized environments. Master’s degree in Computer Science from ITMO University. * Software Engineer specializing in AWS, Kubernetes (with operators), CI/CD, and data platforms. * Golang and Python programming languages. * 10+ years of experience in large enterprise companies. * Certified in AWS, Kubernetes, Google Cloud Platform and Jenkins. * Open source Epiphany project contributor in 2020-2022 - GitHub: epiphany-platform/epiphany Feel free to contact!

Hello! I’m a DevOps Engineer focused on helping teams build efficient, automated, and reliable cloud environments. My goal is to simplify your infrastructure, speed up deployments, and keep everything running smoothly — so you can focus on building great products. I work with modern DevOps tools and technologies, including AWS, Docker, Kubernetes, Terraform, Jenkins, and scripting in Bash and Python. Here’s how I can help your business: - Build and maintain CI/CD pipelines for faster, safer deployments - Design and optimize cloud infrastructure for scalability and cost-efficiency - Implement monitoring, logging, and security best practices - Automate repetitive tasks to improve developer productivity If you’re looking for someone reliable who can turn complex infrastructure challenges into simple, automated solutions — I’m here to help. Let’s discuss how I can add value to your next project!

I take end-to-end ownership of AWS production infrastructure at scale, from Kubernetes and Terraform to CI/CD, security and low-downtime migrations, cutting costs by up to 40% and speeding production deployments 5x. I act as the AWS DevOps lead and technical owner for each project, responsible for architecture, technical decisions, implementation oversight and production delivery. I have delivered more than 10 complex AWS and cloud infrastructure projects for B2B SaaS, B2C products and AI startups. 📈 Selected Results ✅ Reduced AWS infrastructure costs by up to 40% through architecture review, terraform and IaC improvements ✅ Cut infrastructure provisioning time from 4 hours to 20 minutes using terraform and reusable IaC modules ✅ Reduced deployment time from 40 minutes to 8 minutes with CI/CD automation ✅ Built and maintained more than 100 CI/CD pipelines ✅ Automated up to 80% of recurring DevOps work with IaC, terraform and policy-based controls ✅ Completed AWS and kubernetes production migrations with under 5 minutes of downtime ✅ Deployed and improved production kubernetes environments across AWS EKS and k8s clusters ✅ Standardized docker build, release and rollback workflows ✅ Improved cloud security controls and SOC 2 readiness for production workloads ✅ Added automated backups, tested recovery and rollback procedures supporting SOC 2 requirements 🎯 How I Can Help 🔹 Work as your AWS DevOps Engineer to stabilize production infrastructure and resolve recurring operational issues 🔹 Support AWS design decisions as an AWS DevOps Engineer focused on reliability, cloud security and growth 🔹 Deploy and harden kubernetes environments, including k8s on Amazon EKS 🔹 Improve docker images, registries, runtime standards and deployment safety 🔹 Build CI/CD workflows for testing, releases and rollback 🔹 Deliver terraform and IaC changes with reviewable plans and controlled rollout 🔹 Migrate applications and infrastructure with minimal downtime across EKS and k8s environments 🔹 Implement monitoring, alerting, backups and disaster recovery for docker and cloud workloads 🔹 Reduce cloud costs through right-sizing, architecture cleanup and automation 🔹 Prepare cloud security controls and evidence for SOC 2, HIPAA, ISO 27001, GDPR and PCI DSS audits 🛠 Core Stack 🔸 AWS | EKS, ECS, EC2, Lambda, RDS, Aurora, S3, CloudFront, IAM, Route 53, WAF, Security Hub 🔸 kubernetes | EKS, AKS, GKE, Helm, Argo CD, GitOps, ingress, autoscaling, k8s operations 🔸 Infrastructure as Code | terraform, Terragrunt, CloudFormation, Ansible , IaC standards 🔸 CI/CD | GitHub Actions, Jenkins, Azure DevOps, CircleCI, gitlab ci/cd mlops 🔸 Containers | docker, ECR, image scanning, registry policies 🔸 Observability | Prometheus, Grafana, CloudWatch, Datadog, Sentry, OpenTelemetry 🔸 cloud security | IAM, RBAC, secrets management, vulnerability scanning, DevSecOps controls, SOC 2 support 🔸 Data Services | PostgreSQL, RDS, Aurora, Redis, DynamoDB, OpenSearch 🔸 Systems | Linux, Nginx, Bash, Python My work may overlap with senior Full Stack Developer teams and roles such as AWS Architect, Azure Architect, DevOps Kubernetes and cloud engineer. I also support aws lambda, cloud migrations and ci cd delivery when these are part of the project scope. AWS is my primary cloud. I also work with Azure and GCP when the project includes an existing multi-cloud environment, migration or platform-specific requirements. ⚙️ How I Work 1️⃣ As your AWS DevOps Engineer, I review the current architecture, kubernetes platform, docker workloads, cloud security risks and bottlenecks 2️⃣ As your AWS DevOps Engineer, I define priorities, terraform changes, IaC scope, SOC 2 requirements and expected outcomes 3️⃣ As your AWS DevOps Engineer, I improve infrastructure, CI/CD, k8s operations and SOC 2 controls 4️⃣ As your AWS DevOps Engineer, I test docker deployment, rollback, backup and recovery procedures 5️⃣ As your AWS DevOps Engineer, I deliver clear documentation for k8s, IaC and cloud security handover You work directly with me throughout the project. I remain responsible for communication, delivery quality and final technical decisions. For larger scopes, trusted DevOps specialists can support execution under my technical supervision. I remain your main point of contact and responsible for delivery. My delivery process includes k8s review, docker release checks, pipeline validation, SOC 2 evidence mapping and cloud security verification before handover. 💬 Tell me what is happening with your infrastructure, where the risks or bottlenecks are, and what outcome you need. Send me a message, and we can review the problem and discuss the next steps on a call.

I'm Vlad Rybnik, and I'm your guide to the world of reliable cloud platforms. With over 5 years of experience in commercial development and more than 11 years in IT infrastructure, I've learned one thing: stability is not a luxury, but a necessity. I help businesses build, scale, and maintain systems that run like clockwork. My main goal is to give you a solution that not only works but also brings value. Whether it's infrastructure automation, deployment optimization, or backend development, I consistently prioritize efficiency and security. My arsenal: ✔Development: Proficient in Python (FastAPI), PHP (Laravel, WordPress), SQL, and Bash. ✔Databases: Work with PostgreSQL, MySQL, MongoDB, and Redis. ✔Cloud & DevOps: I manage cloud environments (AWS, Azure, GCP) and build CI/CD pipelines using GitHub Actions. ✔Infrastructure: Master of containerization with Docker and Kubernetes, building infrastructure as code with Terraform. ✔Monitoring: Set up Prometheus, Grafana, and CloudWatch to always know what's going on. What really sets me apart is my approach. I'm open to new things, find it easy to get along with the team, and am not afraid of complex challenges.

🎁 𝐆𝐄𝐓 𝐘𝐎𝐔𝐑 𝐅𝐑𝐄𝐄 𝐀𝐈 𝐑𝐄𝐀𝐃𝐈𝐍𝐄𝐒𝐒 𝐀𝐔𝐃𝐈𝐓 - send me a message and I'll analyze your stack, data pipelines, and AI use cases. I'm a Machine Learning Engineer & AI Python Developer with 10+ years of experience building Machine Learning systems, AI solutions, AI Agents, and production infrastructure for SaaS, fintech, manufacturing, healthcare, and enterprise companies across the US and Europe. ✅ I work with a team of 90+ engineers across Machine Learning, AI, DevOps, and Backend disciplines. Delivering end-to-end Machine Learning solutions from data pipelines and model development to deployment, monitoring, optimization, and scaling in production environments. 🎯 What I bring to your product as a Machine Learning Engineer and AI Agent Developer: ✔️ Over 10 years of commercial experience as a Machine Learning Engineer, AI Developer, Python Developer, and Data Scientist, building scalable products for startups and enterprise organizations. ✔️ As a Machine Learning Engineer, I design and build production-grade Machine Learning systems using Python, delivering measurable business outcomes. My solutions have improved operational efficiency by up to 200% and reduced infrastructure costs by as much as 55%. ✔️ As an AI Agent Developer, I build AI Agent systems using LangGraph, CrewAI, OpenAI, Claude, Gemini, Llama, and Mistral. I develop multi-agent architectures for customer support, internal automation, and enterprise workflows. ✔️ My AI Agent experience includes AI sales agent systems, AI business development automation, AI agents for Etsy marketing workflows, and AI agents supporting Pinterest marketing operations. ✔️ As an AI Developer, I deliver AI copilots, Generative AI applications, and LLM-powered platforms using GPT-4, GPT-5, Claude, and open-source models integrated directly into business processes. ✔️ As a Machine Learning Engineer and Data Scientist, I specialize in NLP, semantic search, recommendation systems, anomaly detection, Named Entity Recognition, sentiment analysis, and intelligent automation. ✔️ As a Python Developer, I build Retrieval-Augmented Generation (RAG) systems using Pinecone, Weaviate, Chroma, and enterprise knowledge bases connected to SQL, PostgreSQL, MongoDB, and CRM platforms. ✔️ As a Machine Learning Engineer specializing in Computer Vision, I develop object detection, segmentation, OCR, and Document AI systems using YOLOv8, Detectron2, OpenCV, Amazon Textract, and Google Document AI. ✔️ As an AWS DevOps Engineer and Cloud Engineer, I design highly available infrastructure using AWS, Kubernetes, Docker, Terraform, Jenkins, Kafka, Prometheus, Grafana, and NGINX. ✔️ As an Azure DevOps Engineer, I deploy Machine Learning workloads using Azure DevOps, Azure Data Factory, Terraform, and cloud-native deployment strategies for enterprise environments. ✔️ I regularly collaborate with Data Scientists, Data Analysts, Web Developers, Product Managers, and engineering teams to transform prototypes into scalable production systems used by thousands of end users. 📊 My Achievements in Numbers: 🔶 Machine Learning Engineer for Enterprise Support Platform ▪️ Reduced support workload equivalent to 3 full-time employees. ▪️ Decreased response times from hours to seconds. ▪️ Improved customer satisfaction metrics by more than 40%. ▪️ Processed millions of support interactions annually. 🔶 AI Agent Developer for Fintech Company ▪️ Built and deployed multiple AI Agent workflows in production. ▪️ Automated more than 80% of repetitive operational tasks. ▪️ Reduced manual processing time by 70%. ▪️ Increased team productivity across multiple departments. 🔶 Machine Learning Engineer for Manufacturing Company ▪️ Reduced defect escape rates to near zero using Computer Vision. ▪️ Eliminated thousands of hours of manual inspection work annually. ▪️ Improved quality control efficiency by more than 150%. 🔶 AWS DevOps Engineer for SaaS Platform ▪️ Increased deployment frequency from 1 deployment per month to 120. ▪️ Reduced deployment times by 85%. ▪️ Lowered infrastructure costs by 55%. ▪️ Improved platform reliability and scalability across cloud environments. Why should you hire me as your Machine Learning Engineer? ▪️ 10+ years of experience in Machine Learning, AI Development, Python, and Data Science. ▪️ 50+ Machine Learning and AI projects successfully delivered. ▪️ 90+ engineers available for large-scale engagements. ▪️ Experience across SaaS, fintech, healthcare, manufacturing, and enterprise industries. ▪️ Expertise in Machine Learning, AI Agents, Computer Vision, NLP, RAG, and Generative AI. ▪️ Strong background in AWS, Azure DevOps, Kubernetes, and Terraform. ▪️ Hands-on experience taking Machine Learning and AI products from concept to production. If you're looking for a Machine Learning Engineer, AI Agent Developer, AI Developer, Python Developer, or Data Scientist who can design, build, deploy, and scale production-ready AI systems.