Jerome de Dios

Software Engineering

Software Engineer with over 15 years of experience in development and operations, including Java development, and a proven track record supporting high-traffic sports betting platforms. Skilled in system reliability, troubleshooting, cloud engineering, and collaborating effectively in agile environments. A Masterschool Software Engineering Program graduate, with strong skills in Python, Generative AI, and Cloud Engineering. Committed to building intelligent, scalable solutions and contributing to innovative technology teams, while continuing to develop German language fluency.

New Certificate Updates

• Webeet.io Internship Completion Certificates (AI Engineering + Cloud Engineering)

• Webeet Recommendation Letter Download

• Pandas (Data Analysis with Python)

Completed Course: AI Productivity Live Demonstration

New Article: What is Federated Learning? Read the Article

Updated February 2026

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Currently Learning

German Integration Course in progress — weekly lessons, online.

Updated February 2026

Location

Auerbach (Vogtland), Saxony, Germany

job@jeromededios.de

Looking for

Full time position

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GitHub

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Phone Number

+491795213992

Please leave a message in the voicemail.

1 Page Resume App Support/SRE Resume (SEO and ATS)GenAI Resume (SEO and ATS)

Certificates

Internships

Webeet.io – Amsterdam, North Holland, Netherlands

Intern – Software Development / AI / Cloud

September 2025 – November 2025

https://www.webeet.io

AI Engineering Cloud Engineering Webeet Recommendation

Education

MSIT

Master School Institute of Technology – Berlin, Germany

Cloud Engineering & Generative AI Engineering

https://joinmsit.de

Cloud Engineering

Jun 2025 – Nov 2025

AWSInfrastructure as Code (IaC)Cloud ComputingCloud Storage

Generative AI Engineering

Sep 2024 – Jun 2025

Intensive online training in software & AI engineering
Hands-on with Python, APIs, JavaScript, Flask, SQL

PythonOpenAI APILangChainLLMsToken OptimizationText EmbeddingsStreams

Certificate of Completion (German)Certificate of Completion (English)

ADFC

Asian Development Foundation College, Philippines

Bachelor of Science - BS, Computer Science

Sep 2000 – Jun 2004

Projects

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Grocery Web Application

In this project, I deployed a containerized full-stack grocery web app on AWS using Terraform for automated, scalable infrastructure provisioning. Key outcomes: production-ready setup with EC2, RDS, S3, ECS orchestration, secure networking, and JWT user auth. I learned modular Terraform configs, state management across environments, and DevOps practices like CI/CD and Auto Scaling. It reinforced cloud security, containerization, and IaC best practices while tackling challenges like subnet configs, dependencies, and ECS debugging—yielding faster, more consistent, error-free deployments.

Used Terraform for Infrastructure as Code to manage EC2 and RDS resources.Managed scalable EC2 instances with automated provisioning and security via Terraform.”Set up S3 buckets for storage, backups, and Terraform state managementDeployed and maintained RDS PostgreSQL databases with Terraform for secure, optimized performance

Code

Nursing Assistant Application

Built and deployed an AI-powered Nursing Assistant backend with FastAPI, PostgreSQL, and Python, showcasing AI integration, modular APIs, and secure, scalable cloud architectures. It tackles clinical workflow issues like handoffs, reporting inconsistencies, and info gaps to boost healthcare efficiency, accuracy, and patient care. Key features: AI-driven handoffs/report generation, JWT/OAuth2 auth, Pydantic validation, modular endpoints, and Loguru/Logfire logging. Integrated SQLModel/PostgreSQL for reliable data management. As a solo Masterschool AI/Cloud project, it honed AI orchestration, secure dev, and scalable design best practices, overcoming AI integration, auth, and DB consistency challenges.

Python (FastAPI): Used to build a modular, high-performance backend API with dependency injection for maintainable and testable code.SQLModel / PostgreSQL: Used for object-relational mapping and persistent data storage to reliably manage patient records and application data.Pydantic: Applied for data validation to ensure all API requests and responses are clean, consistent, and error-free.OAuth2: Implemented authentication to securely control user access and protect sensitive healthcare data.Generative AI & RAG: Integrated AI-powered chat and report generation to assist nurses with patient interactions and documentation.Logfire & Loguru: Configured structured logging and monitoring to track application behavior and ensure operational reliability.

Code

RAG System – Java & Python Microservices

Built two solo backend projects showcasing scalable API design and AI integration: a FastAPI Microservice and a Spring Boot AI Chatbot. The FastAPI Microservice features modular, async endpoints with dependency injection and RESTful patterns for maintainable, testable microservices—using FastAPI for high-performance APIs, Docker containerization, PostgreSQL/SQLModel storage, and Pydantic validation, plus service routing, auth, and clean separation of concerns. The Spring Boot AI Chatbot combines Spring Boot/Spring AI with OpenAI GPT models for domain-specific chats (e.g., bakery, legal, health assistants), built on Java 17, PromptTemplate, and Maven with a /chat endpoint, modular configs, and easy domain switching. Together, they honed API orchestration, containerization, AI integration, and prompt engineering across Python/Java ecosystems.

FastAPI: Used to build lightweight, high-performance APIs with asynchronous endpoints and dependency injection for modular, scalable microservices.Docker: Used to containerize the microservices, ensuring consistent environments and simplifying deployment and orchestration.PostgreSQL / SQLModel: Used for reliable, persistent data storage and object-relational mapping to simplify database operations within the microservice architecture.Pydantic: Applied for strict data validation and type enforcement, ensuring clean, predictable API requests and responses.Spring Boot: Used to develop structured RESTful APIs in Java with minimal configuration and strong scalability for the AI chatbot service.Spring AI & OpenAI API: Integrated to enable AI-powered conversational features and prompt-based interactions across multiple business domains.PromptTemplate: Used to manage dynamic prompt construction for flexible and reusable AI responses.Maven: Used for dependency management and project build automation within the Spring Boot chatbot application.

Code Code

Instagram Clone

Built a scalable, maintainable Instagram-like full-stack app: React + TypeScript for modular, type-safe component-driven UI; TailwindCSS for responsive utility styling; React Router for seamless navigation. Used Vite for fast builds/HMR and Docker for containerized deployment. Backend: Fastify for high-performance Node.js APIs, MongoDB for flexible data persistence, and JWT for secure sessions. This stack enables efficient, cross-environment scaling and development.

React (with TypeScript): Used to build a dynamic, component-based frontend with type safety, improving code reliability and maintainability.TailwindCSS: Used for responsive, utility-first styling to create a clean, modern user interface with minimal custom CSS.React Router: Implemented to manage client-side navigation smoothly between pages such as feed, profile, and login.Vite: Used for fast development builds and hot module reloading, accelerating frontend iteration and testing.Docker: Used to containerize both frontend and backend, ensuring consistent builds and seamless deployment across environments.Fastify: Chosen for its high performance and low overhead in handling API requests, ideal for real-time data interactions.JWT (JSON Web Token): Implemented for secure, stateless user authentication across frontend and backend services.

Code Code

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Experience

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Software and Cloud Engineer (Internship)

Sept 2025 - November 2025

https://www.webeet.io · Remote

Built features using TypeScript, Fastify, and React with React Router, following Test-Driven Development (TDD) for reliable, maintainable code.
Created secure, scalable, and high-performance solutions with strong data isolation and authentication
Automated complex tasks and improved decision-making by integrating AI workflows with n8n and AI APIs.
Used modern cloud services and CI/CD pipelines for seamless deployment, monitoring, and ongoing app improvements.

Node.jsReact.jsTypeScriptfastifyReact RouterJestAWSTerraform

Professional Development

Dec 2023 - Present

https://joinmsit.de · Remote

Completed an intensive Generative AI software engineering program at Masterschool, learning Python, APIs, JavaScript, Flask, and SQL for real-world applications.
Gained practical AI Engineering skills through hands-on, industry-focused projects.
Building a new life in Germany, balancing family, personal growth, and cultural integration.
Learning German to boost professional opportunities and connect with the local community.

Senior Application Support Engineer

Nov 2021 - Nov 2023

https://sportserve.co · Hybrid

[Infrastructure & Application Monitoring and Support]
Supported critical Sportsbook and Casino apps, ensuring quick updates and issue fixes for users.
Monitored system health (apps, servers, networks), addressing alerts and performance issues promptly.
Managed monitoring tools, tracked KPIs, and worked with vendors on integrations and issue resolution.
[ITSM Processes & Service Management (Internal & Third-Party)]
Oversaw end-to-end incident management within defined SLAs — including issue reproduction, triage, troubleshooting, resolution, and post-incident reviews — for internal systems and external customer-facing applications (Sportsbook & Casino).
Handled problem management, service/change requests, and participated in release cycles. Contributed to the continuous improvement of the internal knowledge base.
[Software Development Lifecycle (SDLC) Support]
Performed deployments (frontend/backend), hotfixes, and related tasks in staging and production environments.
Worked closely with Network, Platform Engineering, and Development teams to resolve production issues, identify recurring problems, and support ongoing infrastructure needs.

PythonGitDockerTechnical SupportAppDynamicsGrafanaElastic Stack (ELK)PRTGIcingaJiraConfluenceOpsgenieCatchpointJenkinsNexus

Site Reliability Engineer

Sep 2019 - Nov 2021

https://sportserve.co · On-Site

Reduced incident recovery time by 40% through automated monitoring and alerting.
Maintained 24/7 sportsbook systems, achieving 99.95% SLA compliance.
Ensured 99.99%+ uptime and high QoS for global sportsbook platforms.
Improved incident response time by 30% by tracking key SLOs and SLIs.
Partnered with sports trading teams to enhance collaboration and reduce silos.
Developed self-healing scripts, cutting manual incident work by 50%.
Led root cause analyses and post-incident reviews to prevent recurrence.
Worked with DevOps and IT teams to ensure smooth releases and production readiness.
Followed strict change management, achieving 0% critical outages during deployments.
Supported 24/7 operations and participated in on-call rotations.
Applied SRE principles to strengthen reliability and operational excellence.
Used tools like ELK Stack, Grafana, AppDynamics, and synthetic monitoring to improve performance.
Automated deployments with Ansible, Jenkins, and Git, reducing release time by 60%.
Used Linux, Bash, Python, and SQL for daily operations and troubleshooting.
Communicated effectively with technical and business stakeholders under pressure.

PythonGrafanaJenkinsPRTGShell ScriptingAnsibleAppDynamicsIcinga