Hello, I'm
Mohammed Saad
Site Reliability Engineer
DevOps | MLOps | Cloud Solutions
Senior DevOps & Site Reliability Engineer with 9+ years of experience specializing in AWS, GCP, and Azure. Expert in CI/CD pipelines, Kubernetes, MLOps, FinOps & cost optimization, and observability-driven infrastructure for scalable, secure, and cost-efficient cloud solutions.
9+ Years
Experience
Cloud Expert
AWS | GCP | Azure
About Me
Passionate technologist driving innovation through automation and reliability
Site Reliability Engineer | FinOps & Cost Optimization | MLOps & Observability
Senior DevOps & Site Reliability Engineer with over 9 years of experience in DevOps, Cloud Engineering, Data Engineering, and MLOps, specializing in AWS, GCP, and Azure. I have a proven track record of designing, deploying, and optimizing cloud-native infrastructure that is scalable, secure, cost-efficient, and highly observable, supporting enterprise and digital-first organizations across industries.
At Hotspex Media, I architected CI/CD pipelines with Cloud Build, GitHub Actions, and Artifact Registry to enable blue-green deployments and zero-downtime updates. My work reduced MySQL downtime by 40%, improved pipeline availability by 15%, and increased monitoring efficiency by 30%. I also delivered sustained cloud cost savings by implementing FinOps best practices, multi-cloud cost visibility with New Relic CCI and Looker dashboards, anomaly detection, and resource rightsizing across AWS and GCP.
Expert in designing Golden Metrics dashboards (latency, traffic, errors, saturation), SLO-driven alerting, and productionizing ML models with automated retraining and drift monitoring. Proficient in Kubernetes, Terraform, Prometheus, Grafana, New Relic, Datadog, and comprehensive MLOps best practices for both traditional applications and AI-driven platforms.
Based in Toronto, Ontario, Canada • Available for Remote Work • Open to Contract and Full-Time Opportunities in MLOps, SRE, DevOps, and Gen AI Development
9+ Years Experience
DevOps, MLOps, Data Engineering, and SRE across multiple industries
Cloud Certified
AWS DevOps Professional, GCP Architect, CKAD
FinOps & Cost Optimization
Multi-cloud cost governance, anomaly detection, and rightsizing
Observability Expert
Golden Metrics, SLO-driven alerts, and unified monitoring dashboards
Experience
9+ years of building and scaling infrastructure
DevOps Engineer
- ▸Led multi-cloud deployments using GCP (Cloud Build, Container Registry, GKE) and AWS, architecting scalable containerized solutions
- ▸Directed CI/CD strategy with Cloud Build, GitHub Actions, and Artifact Registry, enabling blue-green deployments and automated updates
- ▸Achieved 40% reduction in MySQL downtime through effective blue-green deployment strategies
- ▸Implemented New Relic, Grafana, and Prometheus for enhanced monitoring, resulting in 30% increase in real-time monitoring capabilities
- ▸Configured VPCs, load balancers for regional/global deployments and enforced IAM security policies on GCP
- ▸Orchestrated GKE deployments with complete CI/CD pipelines for automated updates and scalability
Data Engineer
- ▸Increased data pipeline availability by 15% resulting in improved system uptime using GCP
- ▸Built and optimized GCP pipelines: Cloud Storage, Dataflow, BigQuery for predictive analytics
- ▸Executed predictive customer churn analysis with Python and machine learning models
- ▸Created dashboards in PowerBI for business insights and data visualization
- ▸Managed Apache Airflow workflows and GKE migrations for scalable data processing
Data Engineer
- ▸Deployed ARIMA forecasting models in Azure, optimizing parameters and scaling via Kubernetes
- ▸Conducted predictive analytics (customer churn, CO₂ emissions) using Python, Logistic Regression, and ARIMA
- ▸Built automated pipelines to load data into BigQuery via Informatica and operationalized workflows
- ▸Integrated PySpark with Cassandra and Hive for scalable ETL/ELT operations
- ▸Connected ML models with SAP datasets to support enterprise reporting and predictive analytics
- ▸Positioned AI/ML services for production through MLOps best practices and containerized deployments
Data Analyst
- ▸Analyzed data for business intelligence and reporting
- ▸Created data visualizations and dashboards for stakeholder insights
- ▸Performed data quality assessment and validation
Software Engineering Analyst
- ▸Developed and maintained software applications
- ▸Collaborated with cross-functional teams on technical solutions
- ▸Implemented software testing and quality assurance processes
Skills & Expertise
Comprehensive technical stack for modern infrastructure and ML operations
Cloud Platforms
Container & Orchestration
CI/CD & Automation
Monitoring & Observability
FinOps & Cost Optimization
Data & ML Tools
Programming & Scripting
Databases & Storage
Security & Networking
Certifications
Certifications & Badges
Industry-recognized certifications demonstrating expertise in cloud, DevOps, and infrastructure
AWS Certified DevOps Engineer - Professional
Amazon Web Services
Google Cloud Professional Cloud Architect
Google Cloud
Certified Kubernetes Application Developer (CKAD)
Cloud Native Computing Foundation
HashiCorp Certified: Terraform Associate
HashiCorp
AWS Certified Solutions Architect - Professional
Amazon Web Services
Microsoft Certified: Azure DevOps Engineer Expert
Microsoft
Portfolio
Selected projects showcasing my expertise
Multi-Cloud CI/CD Infrastructure
Led GCP and AWS multi-cloud deployments with Cloud Build, GKE, and blue-green deployment strategies, achieving 40% reduction in downtime
Predictive Analytics Pipeline (BPCL)
Built and deployed predictive models for customer churn and CO₂ emissions using Python, containerized and scaled on Azure Kubernetes Service
Churn Prediction & Customer Insights
Designed ETL/ELT workflows with Apache Airflow and Dataflow, deployed churn prediction models with CI/CD integration
Enterprise Data Pipeline (GCP)
Built optimized GCP pipelines with Cloud Storage, Dataflow, and BigQuery, increasing pipeline availability by 15%
Monitoring & Observability Stack
Implemented Prometheus, Grafana, and New Relic across multiple projects, achieving 30% increase in monitoring capabilities
ML Integration with SAP Data
Connected enterprise SAP ERP datasets to ML pipelines with PySpark, Cassandra, and Hive. Leveraged Kubernetes for scaling inference services
ML Observability & Performance Monitoring
Enhanced ML-powered data pipelines with Prometheus, Grafana, and New Relic to track latency, throughput, and drift. Built Looker dashboards combining business outcomes with technical ML KPIs
Technical Blog
Sharing insights on DevOps, MLOps, and Cloud Engineering
Effortless Database Migrations in Production with Cloud Run Jobs
Master DevOps Project 4: Learn how to automate database migrations in production environments using Cloud Run Jobs and GCP
Get In Touch
Open to contract and full-time opportunities in MLOps, Site Reliability Engineering, DevOps, and Gen AI Development. Available for remote work.
Contact Information
Feel free to reach out for collaborations, opportunities, or just a friendly chat.