Matt Armstrong
Senior DevOps Manager | Cloud Infrastructure Leader
📍 Holland, OH 43528
DevOps leader with 7+ years of technical experience and 3 years managing high-performing teams, specializing in cloud infrastructure, Kubernetes orchestration, and automation across AWS, GCP, and Azure environments
About Me
I'm a Senior DevOps Manager with over 7 years of specialized experience in cloud infrastructure, container orchestration, and automation. Based in Holland, Ohio, I bring a comprehensive skill set spanning multiple cloud platforms (AWS, GCP, Azure) and deep expertise in Kubernetes and containerization.
With 3 years of team leadership experience, I've successfully managed high-performing teams of 8+ engineers, fostering collaboration and driving technical excellence. My technical foundation includes extensive scripting experience (8 years Shell, 7 years Python), system administration, and a decade of analytical problem-solving.
Beyond traditional DevOps, I specialize in building intelligent automation workflows using n8n and AI integration. I've architected and deployed sophisticated workflows that interface with various APIs including OpenAI, Anthropic Claude, and custom REST endpoints. My expertise includes creating AI-powered automation pipelines for data processing, intelligent decision-making systems, and seamless integration between diverse platforms and services.
I'm passionate about building scalable, reliable infrastructure, mentoring team members, and implementing automation solutions that drive efficiency and reduce operational overhead. Whether it's leading teams, orchestrating complex Kubernetes deployments, optimizing cloud infrastructure, or building next-generation AI workflows, I thrive on solving challenging technical problems and delivering robust DevOps solutions.
Experience
Senior DevOps Manager CURRENT
Current Role
- Leading and managing a high-performing DevOps team of 8+ engineers across multiple cloud platforms (AWS, GCP, Azure)
- Built and fostered a culture of collaboration and transparent communication within the team, improving cross-functional alignment and delivery velocity
- Optimized existing CI/CD pipelines, reducing deployment times by implementing automation best practices and streamlining release processes
- Implemented Agile team management practices including sprint planning, retrospectives, and continuous improvement initiatives
- Architected and oversaw Kubernetes infrastructure management across multi-cloud environments, ensuring high availability and scalability
- Mentored team members on cloud-native technologies, infrastructure-as-code, and DevOps best practices
- Drove strategic technical decisions for infrastructure automation using Python, Shell scripting, and modern DevOps tooling
Senior DevOps Engineer
Previous Experience
- Managed containerized applications using Docker and Kubernetes (7 years)
- Implemented infrastructure automation using Python and Shell scripting
- Administered Linux systems and performed system administration tasks (8 years)
- Configured and maintained NGINX, load balancing, and high availability solutions
- Managed MySQL databases and implemented Elasticsearch solutions
- Utilized Chef for configuration management and software deployment
Systems Analyst / Administrator
Early Career
- Performed system analysis and troubleshooting (10+ years total experience)
- Managed firewall configurations and network security
- Developed automation scripts using PowerShell and Bash
- Utilized Jira for project tracking and time management
Featured Projects
AI-Powered Upwork Job Discovery & Automation System
Architected and deployed an intelligent job discovery system that automatically scrapes, evaluates, and responds to relevant opportunities on Upwork. The solution uses sophisticated n8n workflows integrated with multiple AI models (Claude and GPT-4) to analyze job postings, calculate match scores based on skills and requirements, and generate personalized cover letters. The system processes job postings every 10 minutes, filtering through hundreds of opportunities to identify high-quality matches.
Key features include AI-driven job evaluation with match scoring (8.25/10 accuracy), automated qualification checks, intelligent proposal generation, Slack notifications for immediate action, and comprehensive tracking in Google Sheets. The workflow includes error handling, timestamp validation, duplicate detection, and multi-stage AI review for quality assurance. This automation has reduced job hunting time by 90% while improving proposal quality and response rates, demonstrating the power of AI-enhanced workflow automation for business process optimization.
Comprehensive Home Infrastructure Monitoring Dashboard
Designed and built a comprehensive home infrastructure monitoring system integrating multiple data sources including server metrics (TrueNAS), IoT sensors (water leak detectors, temperature monitors, smart appliances), network monitoring (Pi-hole, Uptime Kuma), and home automation (climate control, power consumption tracking). The unified Grafana dashboard provides real-time visibility into system health, environmental conditions, and network performance with intelligent alerting for critical issues.
The architecture leverages Prometheus for metrics collection, InfluxDB for time-series data storage, and custom API integrations via Node-RED for external services. Key features include CPU/memory monitoring, service uptime tracking with 99.95%+ SLA calculations, temperature monitoring (HVAC, basement freezer), water leak detection across 4 zones, basement appliance power monitoring, internet speed tracking, and battery level monitoring for wireless sensors. This project demonstrates practical application of enterprise monitoring tools for home infrastructure management, combining DevOps best practices with IoT integration.
Project Screenshot
Intelligent Workflow Automation Platform
Built a comprehensive workflow automation platform using n8n that integrates with multiple AI providers (OpenAI, Anthropic Claude) and over 50 different APIs. The platform enables non-technical team members to create sophisticated automation workflows through a visual interface, while maintaining enterprise-grade security and reliability standards.
Key features include intelligent data transformation using AI, automated decision-making based on business rules, seamless integration with existing tools (Slack, Jira, GitHub), and comprehensive audit logging. This platform has automated over 1,000 hours of manual work monthly and serves as the backbone for various operational processes across the organization.