# Christopher Perkins > Full Stack Engineer Location: Breinigsville, Pennsylvania, United States Profile: https://flows.cv/christopherperkins I build full-stack features with a backend brain. Clean APIs, resilient systems, and tools that make engineers faster are my thing. If it touches production, I make it smoother, stronger, and easier to change. I keep one eye on performance, one on developer experience, one on system resilience, and one on the roadmap. (Yep, I wear ๐Ÿ‘“.) ๐Ÿ“– ๐Œ๐ฒ ๐’๐ญ๐จ๐ซ๐ฒ Before engineering, I did IT support for a Nike logistics center, where a broken label printer meant someoneโ€™s shoes werenโ€™t getting shipped. I ended up writing .NET tools to analyze job duplication and document fixes when none existed. Thatโ€™s where I learned the value of root cause analysis and tight feedback loops. From there, I took the long way in. Launch Schoolโ€™s mastery-based curriculum gave me the foundations to think like an engineer, not just how to write code but how to reason about systems. I cleared every assessment on the first try, then jumped into real projects. I helped design a TypeScript-based workflow engine that allowed custom job pipelines to be scripted with real code, contributed to open source tools like the ZenML VS Code extension, and eventually joined a crypto portfolio and risk management SaaS where I led AI-powered feature adoption, migrated Lambda-based ETL pipelines to ECS, and stabilized backend infrastructure. I like small teams, fast iteration, and tough problems with no obvious answers. โš™๏ธ ๐“๐จ๐ฉ ๐“๐ž๐œ๐ก๐ง๐จ๐ฅ๐จ๐ ๐ข๐ž๐ฌ ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž๐ฌ: Go, TypeScript, Python, SQL ๐…๐ซ๐จ๐ง๐ญ๐ž๐ง๐: React, Next.js, MUI, Tailwind ๐๐š๐œ๐ค๐ž๐ง๐: FastAPI, Express, Pydantic, Node.js ๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž๐ฌ: PostgreSQL, MongoDB ๐ˆ๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž & ๐‚๐ฅ๐จ๐ฎ๐: AWS (Lambda, ECS, RDS, S3, CloudWatch, VPC, CDK, CloudFormation, IAM), Terraform, Docker, Redis, Kafka ๐€๐ˆ & ๐€๐ ๐ž๐ง๐ญ๐ฌ: OpenAI API, RAG, Pydantic AI, vector search ๐ƒ๐ž๐ฏ๐Ž๐ฉ๐ฌ & ๐‚๐ˆ/๐‚๐ƒ: DevOps practices, GitHub Actions, Vercel, Stripe, Git, unit testing, observability ๐€๐ซ๐œ๐ก๐ข๐ญ๐ž๐œ๐ญ๐ฎ๐ซ๐ž: Microservices, event-driven systems, serverless, ETL pipelines ๐๐ซ๐ข๐ง๐œ๐ข๐ฉ๐ฅ๐ž๐ฌ: SOLID, clean code, root cause analysis, debugging ๐“๐จ๐จ๐ฅ๐ฌ: VS Code, Slack, Zoom ๐Ÿ’ฌ ๐‹๐ž๐ญโ€™๐ฌ ๐“๐š๐ฅ๐ค If youโ€™ve got a role where shipping smart, scalable systems matters, feel free to message me. Iโ€™d love to hear more. ## Work Experience ### Full Stack Engineer @ Sylvanus Technologies Jan 2024 โ€“ Present | New York, New York, United States I build full-stack features that make crypto portfolio tools easier to use and maintain. That includes leading adoption of AI-driven features, improving system reliability under load, and overall leaving the codebase better than I found it. ๐Ÿ“Œ๐‘๐จ๐ฅ๐ž Sylvanus is a startup helping users analyze and manage risk in digital asset portfolios. On a small, high-trust team, I work with quantitative developers and data engineers on ETL pipelines, data visualization, and backend services that turn analytics into actionable insights. My focus leans backend heavy, using Go, React, and Python, while also shaping infrastructure and guiding the technical side of AI feature integration. I follow SOLID principles to write code that is easy to understand, test, and maintain. ๐Ÿš€ ๐‡๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ Originally hired on contract to address Lambda ETL jobs hitting the 15-minute limit, I migrated them to ECS Fargate to improve reliability and throughput. After consistently delivering across the stack, the team created a full-time position for me, which I was grateful to accept. I resolved recurring memory issues in our Go backend that caused crashes under large data loads. More recently, Iโ€™ve led adoption of AI-powered features into the product using OpenAI, MongoDB vector indexes, and the Pydantic AI agent framework. Whether improving developer experience or stabilizing infrastructure, I aim to build tools that are solid, scalable, and easy to maintain. ๐Ÿ› ๏ธ ๐’๐ญ๐š๐œ๐ค โ€ข ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž๐ฌ: Go, Python, TypeScript โ€ข ๐…๐ซ๐š๐ฆ๐ž๐ฐ๐จ๐ซ๐ค๐ฌ: FastAPI, Pydantic AI โ€ข ๐…๐ซ๐จ๐ง๐ญ๐ž๐ง๐: React, Next.js, MUI, Tailwind โ€ข ๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž: PostgreSQL, MongoDB โ€ข ๐ˆ๐ง๐Ÿ๐ซ๐š๐ฌ๐ญ๐ซ๐ฎ๐œ๐ญ๐ฎ๐ซ๐ž: AWS (Lambda, ECS Fargate, ELB, SNS, CloudWatch), Vercel, Kafka, Redis โ€ข ๐“๐จ๐จ๐ฅ๐ฌ & ๐ˆ๐ง๐ญ๐ž๐ ๐ซ๐š๐ญ๐ข๐จ๐ง๐ฌ: Stripe, GitHub Actions, OpenAI ๐Ÿค ๐‡๐จ๐ฐ ๐–๐ž ๐–๐จ๐ซ๐ค We stay lightweight on process and heavy on ownership. I focus on shipping responsibly, improving systems, and being easy to work with. ### Open Source Developer @ ZenML Jan 2024 โ€“ Jan 2024 I jumped into ZenMLโ€™s VS Code extension as a community contributor and ended up shipping two major features to a tool with over 1,800 downloads. ๐Ÿ“Œ ๐‘๐จ๐ฅ๐ž & ๐‡๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ I worked on two major features for ZenMLโ€™s VS Code extension: a DAG visualizer to help users see their pipeline structure at a glance, and a deployment panel for configuring and managing MLStacks. I started the DAG visualizer by pair coding with another contributor, then finished both features independently. While building them, I ran into and fixed multiple issues, including a bug with Watchdog file change detection and compatibility problems with newer ZenML client versions. I extended the TypeScript frontend, integrated it with the existing Python backend via the Language Server Protocol, and focused on making the experience intuitive for everyday users. The work was unpaid and freelance, but I approached it with the same level of care I bring to production roles. โธป ๐Ÿ› ๏ธ ๐’๐ญ๐š๐œ๐ค โ€ข ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž: TypeScript, Python โ€ข ๐…๐ซ๐š๐ฆ๐ž๐ฐ๐จ๐ซ๐ค: ZenML, Watchdog, Language Server Protocol โ€ข ๐…๐ซ๐จ๐ง๐ญ๐ž๐ง๐: VS Code Extension APIs, HTML, CSS โ€ข ๐“๐จ๐จ๐ฅ๐ฌ & ๐ˆ๐ง๐ญ๐ž๐ ๐ซ๐š๐ญ๐ข๐จ๐ง๐ฌ: ZenML Python Client, GitHub, SVG.js ๐Ÿค ๐‡๐จ๐ฐ ๐–๐ž ๐–๐จ๐ซ๐ค๐ž๐ I started off pairing with another contributor on the DAG visualizer, then took full ownership of both features. I worked independently but checked in regularly with a ZenML engineer. Each feature was scoped, built, and documented with long-term maintainability in mind, and I treated every issue like production work. ### Co-Creator, Software Engineer @ Reverb Jan 2024 โ€“ Jan 2024 I helped build a TypeScript-powered workflow engine focused on fast iteration, clean developer tooling, and asynchronous job orchestration at scale. ๐Ÿ“Œ ๐‘๐จ๐ฅ๐ž Reverb was a small, four-person engineering effort focused on creating a robust workflow engine that prioritized developer experience. The idea was to let engineers define workflows using TypeScript and run them as distributed, event-driven systems without managing orchestration themselves. I worked on backend infrastructure, queue orchestration, API schemas, and deployment tooling. Most of my time went into writing clean, testable services and shaping a platform that felt simple to use but powerful under the hood. We moved quickly and shipped a lot, but the project ultimately didnโ€™t reach production or adoption. ๐Ÿš€ ๐‡๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ I implemented job orchestration logic using Graphile Worker and PostgreSQL, built out API layers with Express, and defined how workflows were represented and triggered. I added developer tooling for debugging and logging, containerized services for ECS, and maintained CI flows with GitHub Actions. I also ran load testing with Artillery.io and handled end-to-end test flows in Postman. Communication between our queue workers and custom workflows was powered by JSON-RPC, which I helped integrate and support. Throughout, I focused on maintainability, clarity, and fast feedback loops. ๐Ÿ› ๏ธ ๐’๐ญ๐š๐œ๐ค โ€ข ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž๐ฌ & ๐…๐ซ๐š๐ฆ๐ž๐ฐ๐จ๐ซ๐ค๐ฌ: TypeScript, Express (Node.js) โ€ข ๐–๐จ๐ซ๐ค๐Ÿ๐ฅ๐จ๐ฐ & ๐ˆ๐ง๐Ÿ๐ซ๐š: Graphile Worker, JSON-RPC, Docker, GitHub Actions, AWS (Lambda, ECS Fargate, RDS) โ€ข ๐ƒ๐š๐ญ๐š๐›๐š๐ฌ๐ž: PostgreSQL, MongoDB โ€ข ๐“๐ž๐ฌ๐ญ๐ข๐ง๐  & ๐“๐จ๐จ๐ฅ๐ฌ: Artillery.io, Postman ๐Ÿค ๐‡๐จ๐ฐ ๐–๐ž ๐–๐จ๐ซ๐ค๐ž๐ We worked in a fast-paced, collaborative environment with daily standups, pair programming, and async communication. I shared ownership of system design and delivery, focusing on clean interfaces and testable systems others could build on. ### Deskside Support Technician @ Stefanini North America and APAC Jan 2021 โ€“ Jan 2024 | Bethlehem, Pennsylvania, United States I built tools, tracked down flaky systems, and wrote the docs we needed. It wasnโ€™t called engineering, but it felt like it: find the problem, script the fix, and leave it better than before. ๐Ÿ“Œ ๐‘๐จ๐ฅ๐ž At Stefanini, I supported a high-volume Nike logistics hub by diagnosing and resolving hardware, software, and network issues across the warehouse and office. Most of my time went into solving recurring problems, documenting effective fixes, and figuring out why issues happened in the first place. That root-cause-first mindset (breaking down problems, isolating variables, and testing until the issue was clear) now serves me in software just as well. ๐Ÿš€ ๐‡๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ I streamlined support for a persistent duplicate print issue by writing a C# program that scanned DMP spool files for repeated jobs. That surfaced a timeout-triggered failover to a second print server, which we were then able to resolve. I also wrote a C# tool to poll Zebra printers for label usage data, giving the team better visibility into supply levels. When recurring issues lacked documentation, I created internal guides for common problems with monitors, docks, and label printers so tickets could be closed faster and with more confidence. ๐Ÿ’ป ๐“๐ž๐œ๐ก๐ง๐จ๐ฅ๐จ๐ ๐ฒ โ€ข ๐‹๐š๐ง๐ ๐ฎ๐š๐ ๐ž๐ฌ & ๐’๐œ๐ซ๐ข๐ฉ๐ญ๐ข๐ง๐ : C#, PowerShell, Windows Batch โ€ข ๐๐ฅ๐š๐ญ๐Ÿ๐จ๐ซ๐ฆ๐ฌ & ๐“๐จ๐จ๐ฅ๐ฌ: .NET, Azure, Active Directory, Microsoft Office โ€ข ๐’๐ฎ๐ฉ๐ฉ๐จ๐ซ๐ญ ๐’๐ฒ๐ฌ๐ญ๐ž๐ฆ๐ฌ: ServiceNow ๐Ÿค ๐‡๐จ๐ฐ ๐–๐ž ๐–๐จ๐ซ๐ค๐ž๐ I collaborated with warehouse control systems, networking, and operations teams. We met daily for standups and used ServiceNow to manage tickets and escalate site-wide issues. ## Education ### Mastery-Based Learning Program - Ruby Track Launch School Jan 2022 โ€“ Jan 2023 ## Contact & Social - LinkedIn: https://linkedin.com/in/christopher-r-perkins - Website: https://reverb-app.github.io --- Source: https://flows.cv/christopherperkins JSON Resume: https://flows.cv/christopherperkins/resume.json Last updated: 2026-04-01