andrew espira
Platform Engineer | Specializing in DevOps and Site Reliability Solutions
© 2025 Espira. All Rights Reserved
Introduce
Hello,I'm Espira Building Tomorrow's Infrastructure Today | Specializing in DevOps, Platform and Site Reliability Solutions
I'm passionate about creating and optimizing the technological foundations that businesses rely on, turning complex infrastructure challenges into elegant, efficient solutions that scale seamlessly and perform reliably
8+
Years of
Experience
30+
projects completed on
different technologies
About
Every great system scales with purpose,
let's build yourfuture
Drawing on eight years of experience in large-scale infrastructure and reliability engineering, I've mastered the art of building and maintaining infrastructure at scale. From orchestrating distributed cloud architectures to deploying AI infrastructure and GPU clusters, I combine technical precision with innovative solutions to drive operational excellence.
Resume
Education & Experience
Graduate Student, Data Science
Saint Peter's University, New Jersey
BSc in Computer Technology
Jomo Kenyatta University of Agriculture and Technology
Professional Certifications
View my verified achievements on
Credly BadgesThis link leads to the Credly platform where I have listed all my professional certifications and badges that showcase my specialized skills.
Site Reliability Engineer, Data Streaming Team
Sport Server
- Directed SRE initiatives to ensure high reliability and performance of data streaming systems.
- Optimized BigQuery infrastructure, resulting in reduced processing times and enhanced query efficiency.
- Implemented cost management strategies, achieving a 30% reduction in operational expenses.
- Designed and deployed a comprehensive observability framework utilizing Google Cloud Platform tools.
Research Software Engineer, Infrastructure
Eco Health Alliance
- Architected scalable serverless infrastructure on AWS, enhancing system scalability and reducing costs by 30%.
- Developed robust data collection and warehousing systems tailored to field research requirements.
- Managed high-performance computing environments using Docker and orchestration tools, improving reliability during peak workloads.
- Led the deployment of Large Language Models (LLMs) on GPU clusters, advancing machine learning capabilities.
- Automated infrastructure deployment processes, increasing operational transparency and reducing manual workload by 40%.
Site Reliability Engineer
Sport Server
- Managed large-scale, high-availability sports server infrastructure on Google Cloud Platform, maintaining 99.9% uptime and 99.95% data integrity.
- Oversaw the full service lifecycle, from design to continuous improvement, ensuring robust and scalable architecture.
- Integrated Google Cloud tools to enhance data observability and enable real-time quality checks.
DevOps Technical Lead
Sarami · Contract · Nairobi, Kenya
- Developed and executed software release management strategies, including migration of applications from Heroku to AWS.
- Implemented autoscaling, load balancing, and managed DNS using AWS Route 53 to ensure high availability.
- Increased automation through GitHub Actions and Jenkins, and managed Kubernetes deployments via GitOps methodologies.
- Engineered secure systems on AWS, leveraging services such as Amplify, EC2, S3, ELB, and CloudFormation.
- Utilized AWS SDK in Python to automate cloud operations, reducing configuration errors and deployment times.
- Enhanced application performance through microservices architecture and improved system observability using APM tools.
System Engineer
ICIPE - International Centre of Insect Physiology and Ecology
- Upgraded AWS-based computing platforms to improve scalability and efficiency for scientific computations.
- Streamlined big data analysis and deployment processes using Slurm and Terraform.
- Developed and maintained genomic data analysis pipelines, enhancing data reusability and research productivity.
- Collaborated with technology vendors to minimize system failures and improve infrastructure reliability.
- Implemented performance monitoring solutions with Grafana, ensuring system health and uptime.
Data Systems Consultant
ICIPE - International Centre of Insect Physiology and Ecology
- Optimized data processes for scalability, increasing the efficiency of data operations for research teams.
- Developed analytical tools to generate actionable insights, supporting strategic decision-making.
- Integrated and built data analytics platforms tailored for entomological research.
- Designed machine learning models for real-time monitoring of insect populations, improving research accuracy.
DevOps Engineer
ICIPE - International Centre of Insect Physiology and Ecology
- Architected and deployed comprehensive CI/CD pipelines using Jenkins and CircleCI, enabling real-time monitoring and cloud integration.
- Developed and managed Docker and Singularity containers, orchestrating deployments across Kubernetes clusters for scalable infrastructure.
- Administered high-performance computing (HPC) environments, supporting complex data processing tasks.
- Optimized batch queuing systems in a massively parallel production setting, increasing processing efficiency and throughput.
- Conducted system utilization analysis to ensure over 90% uptime and robust system health.
- Led infrastructure redesign initiatives, automating core processes and enhancing scalability, reducing operational overhead.
- Constructed advanced SQL-based infrastructure for data extraction and loading, developing analytical tools to transform data into actionable intelligence.
- Collaborated with executive, product, data, and design teams to address infrastructure needs and technical challenges.
- Implemented and continually refined data management procedures, improving data system functionality for ongoing research and operations.
Services
My Specializations
Cloud Computing
Proficient in deploying and managing scalable cloud solutions across AWS and GCP, my expertise encompasses a wide range of cloud technologies. I focus on aligning with the pillars of the Well-Architected Framework to ensure operational excellence, security, reliability, performance efficiency, and cost optimization in diverse cloud environments.
Multiple ProjectsKubernetes & Containerization
Proficient in advanced container orchestration techniques with Kubernetes, enhancing cloud-native applications' scalability and resilience.
Multiple ProjectsObservability & Monitoring
Specialized in designing high-performance data observability frameworks, I focus on leveraging cutting-edge technologies for comprehensive system monitoring, ensuring enhanced visibility and operational insights across various cloud environments
Multiple ProjectsBig Data & Data Engineering
Specialized in big data technologies and data engineering, optimizing data processes for scalability and efficiency across distributed systems.
Multiple ProjectsCI/CD Pipelines
Skilled in enhancing software development and delivery through the automation of deployments with CI/CD pipelines, ensuring streamlined and efficient processes across development environments. I incorporate rigorous security checks to maintain high standards of software integrity and security
Multiple ProjectsLarge Scale Distributed Computing
Experienced in managing complex, large-scale distributed computing environments to support intensive data processing and analysis tasks.
Multiple ProjectsMachine Learning & AI
Skilled and experienced in orchestrating the deployment and integration of Large Language Models (LLMs) and machine learning solutions within GPU-accelerated environments, enhancing performance and driving innovative data processing capabilities
Multiple ProjectsInfrastructure as Code
Skilled and experienced in applying Infrastructure as Code (IaC) methodologies across diverse platforms, from cloud environments to bare metal clusters. My approach automates the provisioning and management of resources, ensuring consistency, scalability, and compliance across all operational environments.
Multiple ProjectsMy Skills
My Technical Proficiencies
GPU Computing & AI Infrastructure
- GPU Resource Management, CUDA, Performance Optimization
- Kubernetes GPU Operator, Resource Scheduling
- Machine Learning Infrastructure, Model Deployment
Programming Languages
- Python, Java, Golang, JavaScript, R, Rust
Containerization & Orchestration
- Docker, Singularity, Kubernetes, Docker Swarm
Infrastructure as Code
- Terraform, Ansible, Helm
Cloud & Infrastructure
- AWS, GCP, Kubernetes, Terraform
- Infrastructure as Code, GitOps
- High Availability Architecture
CI/CD Tools
- Jenkins, CircleCI, GitHub Actions
Monitoring and Logging
- Grafana, Prometheus, ELK Stack, Open Telemetry, Honeycomb
Distributed Systems
- Distributed Computing, Scalable Architecture
- Message Queues, Event-Driven Systems
- Consensus Protocols, Eventual Consistency
Database Management
- PostgreSQL, MongoDB, MySQL, Cassandra
Server Management & Version Control
- Linux, Windows, GitHub, GitLab
Project Management Tools
- Asana, Jira, Confluence, Opsgenie
Portfolio
Featured Projects
Model Drift Detection in Streaming AI Systems
Developed a real-time system for detecting and responding to model drift in streaming data environments. The project implements a data mining pipeline for detecting distribution shifts in streaming feature data, leveraging Kafka for data streaming and applying statistical methods such as Jensen-Shannon divergence and mean shift detection. Features real-time dashboards and adaptive thresholding for robust monitoring and alerting.
Technologies: Kafka, Python, Statistical Analysis, Real-time Dashboards
Log Insights: AI-Powered Log Analysis
Engineered an intelligent log analysis tool that leverages large language models (LLMs) to provide deep insights into system logs. The platform identifies issues, patterns, and anomalies, performs root cause analysis, and offers remediation suggestions. Features real-time visualization of log patterns and supports various log formats for flexible integration.
Technologies: Python, OpenAI GPT, Data Visualization, Log Parsing
Scalable Distributed Key-Value Store
Implemented a highly available distributed key-value store with eventual consistency, featuring consistent hashing, replication, vector clocks, and gossip protocols. The system ensures data durability and handles node failures gracefully while maintaining uptime. Designed for scalability and high availability in cloud-native environments.
Technologies: Go, AWS, Kubernetes, Distributed Algorithms
Bankruptcy Prediction with Machine Learning
Developed a machine learning pipeline for predicting bankruptcy using financial datasets. The project includes feature engineering, model selection, and evaluation with a focus on explainability and robust prediction. Utilized advanced ML techniques to improve prediction accuracy and support financial risk assessment.
Technologies: Python, Scikit-learn, Data Engineering, Financial Analytics
Advanced Data Observability
Developed comprehensive observability solutions using Google Cloud Platform (GCP) tools such as BigQuery, Cloud Logging, and Stackdriver. These solutions enabled real-time data analytics, log management, and monitoring to ensure system reliability and performance. Implemented automated alerting and dashboards using Grafana to provide actionable insights and improve operational efficiency.
Tools Used: GCP, BigQuery, Cloud Logging, Stackdriver, Grafana, Python, Java.
Healthcare Service Clinical Workflow System
Developed a comprehensive healthcare service management system that streamlines the entire patient care workflow from referral to payment completion. This system ensures regulatory compliance while optimizing service delivery efficiency.
- Automated critical processes including referral management, insurance verification, and authorization tracking
- Implemented real-time compliance monitoring with automated checkpoints
- Built intelligent alert systems for deadline management and documentation requirements
- Created detailed audit trails for regulatory compliance
- Integrated billing and claims management with automated verification
Technologies: React, Node.js, PostgreSQL, Redis, Docker, AWS Services
Cross-platform Store Management System
Engineered a comprehensive store management application that streamlines daily operations and financial tracking. This cross-platform solution provides robust business process automation with a focus on user-friendly operation.
- Built with Electron and React for seamless cross-platform compatibility
- Implemented sophisticated state management using Redux for reliable data handling
- Designed a normalized SQLite database schema for efficient data organization
- Created automated systems for tax calculations and financial reconciliation
- Developed robust backup systems and data export capabilities (CSV/PDF)
Technologies: Electron, React, Redux, SQLite, Node.js, Material-UI
Microservices Monitoring with OpenTelemetry
Implemented OpenTelemetry for distributed tracing and monitoring across a microservices architecture. Utilized application performance management (APM) tools to collect and analyze telemetry data, providing deep insights into system performance and enhancing reliability. Integrated with existing monitoring solutions like Prometheus and Grafana to visualize and manage service health.
Tools Used: OpenTelemetry, Prometheus, Grafana, Python, Docker, Kubernetes.
NLP and Large Language Model Deployment
Focused on leveraging large language models (LLMs) and natural language processing (NLP) techniques to extract and structure data from unstructured text sources. Conducted intensive model training on localized GPU setups to enhance processing efficiency and accuracy. Developed pipelines for fine-tuning models to specific datasets and tasks, improving their applicability in real-world scenarios.
Tools Used: Python, TensorFlow, PyTorch, GPU Computing, Docker, Kubernetes.
Enterprise Cloud Migration
Managed a major cloud migration project to Amazon Web Services (AWS), utilizing Infrastructure as Code (IaC) tools such as Terraform to ensure a smooth and efficient transition. Implemented automated deployment pipelines using CI/CD tools like Jenkins and GitHub Actions. Enhanced operational efficiency and scalability by leveraging AWS services such as EC2, S3, and RDS.
Tools Used: AWS, Terraform, Jenkins, GitHub Actions, Python, Docker.
High-Performance Computing Setup
Designed and optimized a Kubernetes-based High-Performance Computing (HPC) environment for complex data analysis tasks. Managed container orchestration using Docker and Kubernetes to ensure efficient resource utilization and scalability. Integrated with parallel computing frameworks and batch scheduling systems for optimized performance.
Tools Used: Kubernetes, Docker, Slurm, Terraform, Python, R, Ansible.
Data Security Enhancement Initiative
Led the development and implementation of advanced security measures to protect sensitive data. Utilized AWS security services, encryption techniques, and continuous monitoring to ensure data integrity and compliance with industry standards. Implemented automated security checks and incident response protocols to enhance overall security posture.
Tools Used: AWS Security Services, Python, Terraform, Jenkins, ELK Stack.
Prompt-Engineering for Open-Source LLMs
Developed prompt-engineering techniques for enhancing the performance of open-source large language models (LLMs). Implemented and fine-tuned prompts to improve the accuracy and applicability of LLMs in various use cases, such as text summarization, sentiment analysis, and information extraction.
Tools Used: Python, TensorFlow, PyTorch, OpenAI GPT, Docker.
Dockerized Jupyter Notebooks Setup
Created a Dockerized environment for running Jupyter notebooks, enabling easy sharing and consistent setups across teams. Utilized Docker Compose for managing multiple containerized environments, simplifying the deployment and maintenance of Jupyter notebooks for data science and research projects.
Tools Used: Docker, Docker Compose, Jupyter, dockerswarm, EKS, Python.
AWS ParallelCluster Setup
Implemented AWS ParallelCluster for managing High-Performance Computing (HPC) clusters, supporting various instance types and job schedulers like AWS Batch and Slurm. Developed and maintained HPC infrastructure to enable scalable and efficient computational workflows for research and data-intensive applications.
Tools Used: AWS ParallelCluster, AWS Batch, Slurm, Python, Terraform.
Serverless Architecture Migration
Migrated applications to a serverless architecture using AWS Lambda, CloudFront, Cognito, API Gateway, and integrated monitoring with AWS CloudWatch and X-Ray for scalability and performance. This approach aimed to achieve cost efficiency, high availability, and enhanced security for cloud-based applications.
Tools Used: AWS Lambda, CloudFront, Cognito, API Gateway, CloudWatch, X-Ray, Terraform, Python, MongoDB.
Let's Connect
Ready to Build Scalable Solutions?
From Infrastructure to Innovation: Let's Transform Your Vision
Specialized In:
- Cloud Architecture & Infrastructure
- AI/ML Systems & GPU Computing
- Distributed Systems & Scalability
- DevOps & Site Reliability Engineering
Whether you're scaling your infrastructure, optimizing performance, or implementing cutting-edge AI solutions, I bring the expertise to make it happen. Let's discuss how we can achieve your technical goals while ensuring reliability, scalability, and innovation.
Email: masundeespira@gmail.com
Phone: +5518041964
GitHub: github.com/espirado
LinkedIn: linkedin.com/in/andrew-espira
Let's Collaborate On:
- Building Resilient Cloud Infrastructure
- Scaling Distributed Systems
- Optimizing AI/ML Platforms
- Enhancing System Performance
- Implementing Site Reliability Best Practices
- Designing High-Performance Architecture
Ready to get started? Let's discuss your project needs.
Schedule a Consultation