Software Engineer
Pasadena, CA
Email: daniel AT daniel-gerst DOT com
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GitHub
I'm a software engineer and recent UC Santa Cruz Computer Science graduate. I work across full-stack development, cloud infrastructure, and automation — from enterprise systems at Cisco to startup work at Orbee. This is my plain little corner of the web.
Skills: Jira Automation, Jenkins, AWS Lambda, GitHub Actions, Groovy, Python, AI Automation, Atlassian Rovo Agents, Glean Agents.
Restored a neglected internal dashboard used by senior leadership to monitor code-quality metrics — comprehensive analysis, bug fixes, automated database resets, and intelligent error-logging with email notifications. Redesigned the Jenkins-based Build Acceptance Test scripts that certify deployments to customer production environments, adding dropdown interfaces for Deploy/Canary/Failover and Groovy automation that removed manual steps and enabled clean hand-off to support teams. Worked across defect tracking, static code analysis, agile planning, and automated-testing frameworks while supporting the IoT team.
Built back-end services in Ruby on Rails and AWS Lambda to asynchronously process and transfer large volumes of customer data to and from an outside organization, following internal standards for secure, compliant data handling. Containerized applications with Docker for consistent deployments and automated developer workflows with custom Bash scripts.
Portfolio site with an AI-powered recruiter tool and an embedded live-coding environment. The recruiter tool generated tailored summaries via the OpenRouter API (DeepSeek), with deterministic keyword matching across 200+ technical skills. Ships through a GitHub Actions pipeline to Firebase Hosting with TypeScript compilation, Functions deployment, and Cloudflare DNS. (This current page is the retro rebuild of that site.)
Stack: HTML5, CSS3, JavaScript, Firebase Functions, TypeScript, OpenRouter API, GitHub Actions, Cloudflare DNS.
Blockchain-security platform that protects token airdrops from Sybil attacks. It visualizes wallet interactions, detects fraudulent patterns with the Louvain community-detection algorithm, scores risk from graph context, and flags suspicious accounts in real time — improving token-distribution fairness by separating genuine users from attackers.
Stack: React, TypeScript, Material UI, D3.js, Python, Flask, FastAPI, Neo4j, Moralis.
Implemented depth-first, breadth-first, and A* search for a Pac-Man competition against other students using adversarial AI models, based on the UC Berkeley Pac-Man projects.
A Tinder-like mobile app that makes the internship search enjoyable: swipe through tech internships, manage an account, and save roles you swipe right on. Built in a team of five using Agile (three weekly scrums, pair programming, Jira, GitHub) with a Firebase backend.
Stack: React Native, JavaScript, Expo, Firebase, Firestore, Python.
With a group of four, built a Py4Web + Firebase platform to catalog rare bird sightings with real-time location mapping via the Google Maps API, plus statistics, data visualization, and a user leaderboard.
Languages & Databases: Python, Ruby, Java, JavaScript, TypeScript, Haskell, C, HTML, CSS, SQL, Apache Groovy, Bash, MongoDB, Firebase.
DevOps: Jenkins, Ansible, SonarQube, Docker, AWS Lambda, Selenium.
Frameworks & APIs: React, Ruby on Rails, Py4Web, Flask, Angular, Postman, RESTful APIs.
Operating Systems: Windows, Linux (Ubuntu, Kali), macOS.
Other Tools: Wireshark, Ghidra, Splunk, VirtualBox, OpenSSH.