Cloud & AI Solutions Enginee
Sergey Molkov
About me
Hi! I'm Sergey Molkov.
I am a Cloud & AI Solutions Engineer with hands-on experience in Microsoft Azure and Amazon Web Services (AWS), and a growing focus on Applied AI and Machine Learning.I specialize in designing and maintaining cloud architectures, network configuration, infrastructure migration, automation (Terraform, ARM/Bicep, CloudFormation), containerization (Docker, Kubernetes/AKS/EKS), and building secure, highly available solutions. Alongside cloud engineering, I apply machine learning techniques — data preprocessing, feature selection, classification, and ensemble modelling — to build intelligent, data-driven systems.I apply Azure Well-Architected and AWS Well-Architected Framework principles to ensure high-quality and predictable infrastructure. I excel in problem-solving, quickly identifying optimal technical solutions, and collaborate effectively within cross-functional teams.My work is focused on stability, security, cost optimization, and scalability.
My skills
- Foundational IT Knowledge: Windows Server, Linux
- Programming Languages: Python, Bash
- Data Science & ML: Python (Pandas, NumPy, Scikit-learn, LightGBM, Matplotlib)
- Cloud Technology: Azure, AWS
- Infrastructure as Code: AWS CloudFormation, Terraform
- Containers and Container Orchestration: Docker, Kubernetes
- Cloud Application Architecture: Microservices, Serverless, CI/CD
- Networking: TCP/IP, DNS, VPN, Firewall
- Database Languages: PostgreSQL, SQL
Hands-on projects
1. Production-grade 3-Tier Architecture on Microsoft Azure
A secure, scalable 3-tier cloud architecture on Azure, including Azure App Service frontend, private AKS backend with Internal Ingress, and Azure SQL via Private Endpoint, all routed through Azure Front Door Premium with end-to-end Private Link and strict network isolation.2. Secure Enterprise Environment in Azure
Azure AD with MFA and Conditional Access, Key Vault for secrets management, disk and database encryption, Azure Defender + Sentinel for threat detection, Network Security Groups, Azure Firewall, and Azure Policy for enforced compliance.3. Python Hands-on Projects
A collection of applied ML and data science projects: data preprocessing (SimpleImputer, IterativeImputer), COVID-19 exploratory analysis, real estate price prediction (Linear Regression), automated multi-method feature selection tool (Pearson, Chi-Square, RFE, Lasso, Random Forest, LightGBM), Random Forest hyperparameter tuning with RandomizedSearchCV, customer classification with a Voting Ensemble, and a Selenium-based Yelp review scraper.
Education
Applied A.I. Solutions Development Graduate Certificate
George Brown College, Toronto, ON
- Developing and deploying AI, machine learning and deep learning systems
for industry-specific use cases across the full production lifecycle.
- Evaluate and manage data sources; design storage architectures
and data-driven solutions to meet business requirements.
- Build and deploy ML/deep learning models using mathematical algorithms,
frameworks and tools for classification, feature selection and analytics.
May 2026 – Apr 2027
Cloud Computing Technologies Graduate Certificate
George Brown College, Toronto, ON- Create secure, highly available micro-services and enterprise-level applications in cloud environments such as Azure and AWS to meet client needs and business requirements.
- Using configuration management and automation tools to provision and manage IT networks and systems on-prem and in cloud environments.
May 2025 – Apr 2026
Certification
November 2025
August 2025
Experience
Branch Manager
Russian TV and Radio broadcasting company, Russia- Optimized staff size and processes, resulting in a 15% increase in broadcast stability metrics and operational efficiency.
- Introduced three new services to the revenue portfolio, driving a 2% annual revenue growth through cross-functional collaboration.
- Led the branch to win awards as the best among large branches twice, demonstrating strong project management and team coordination skills
Sept 2011 – March 2025