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Intro #

HI! Welcome to my blog/portfolio…thing.

New York-based SRE and infrastructure engineer. Previously fullstack and ecommerce, now focused on Linux systems, Kubernetes, and building tooling that makes complex systems manageable.

Professional Experience #

  • Ecommerce: inventory systems (SKU management and tracking), created APIs that helped shape user UX to increase sales (e.g.: quick-add items w/ only 6 left in stock to cart right before checkout), financial reports, UX adjustments to help sales productivity.
  • SRE: CI/CD pipelines for application deployments (emphasis on sub-10 minute recovery times for outages). Testing libraries and harnesses (this is BEFORE LLMs) Security audits (routed requests for PEN testers). Scaled deployments for applications (e.g.: goin from deploy once a month to multiple times a DAY), eventually scaling and standardizing practices across multiple teams and BUs.
  • Ops: Infrastructure A/B automations for 0-downtime cluster cutovers. AWS (cloudformation), Chef, Ansible, terraform; now ArgoCD and K8s. Implemented OTeL monitoring and alerting (Prometheus, Grafana, Alertmanager). Outage triage, direction, RCA composition/writeups.
  • SWE: full-stack - front-end is admittedly my weakpoint (latest experience in TS React, Spotify backstage). Have written various applications to sensibly wrap all systems that I’ve worked on above, in a myriad of flavors (MVC monoliths, to microservice-based workflow systems).

Current focus: shared LLM memory/context architectures and GitOps pipelines for AI workloads.

The above is a very abbreviated splurge of my experience using and developing proprietary software! For more details, you’ll have to speak to me face-to-face ;)

Personal/FOSS Work #

Homelab & Infrastructure: I run a TalosOS Linux Kubernetes cluster on Raspberry Pi 5s, managing ~30 application services via ArgoCD GitOps. See my project entry on my homelab for more details!.

LLM Ops: Running local inference experiments with Qwen 3.6 models (llama.cpp vs vLLM), speculative decoding, and quantized MoE models on consumer hardware. This entire site was coded with qwen3.6-35b-a3b :D

Automation Tooling: Built nox-bot — a Go CLI for Telegram messaging, LLM-powered service reports, and homelab automation. Also maintain pinchscrape (OPML feed scraper) and various utility scripts (luks-utils).

Infrastructure as Code: Documented my Talos Linux + K8s homelab setup for others to replicate. Contributing to the Talos ecosystem through configuration examples and operational runbooks.

Open Source & Community: Arctic Code Vault Contributor - code archived at Svalbard. Pull Shark x3 (100+ PRs opened). Active contributor across Adobe, Behance, and Adobe Platform orgs on GitHub. I maintain helm-charts for any services that I self-host in my homelab!

Skills #

Infrastructure: Linux (RHEL, Debian, Alpine, Arch/CachyOS), Kubernetes, Talos Linux, Docker, Ansible, Terraform, Vault, Traefik, Longhorn, CNPG, NUT UPS, AWS

CI/CD & GitOps: GitHub Actions, Flux CD, Argo CD, Helm, Kustomize, Gitea

AI/ML Ops: llama.cpp, OpenAI-compatible APIs, speculative decoding, quantized MoE models, LLM-assisted development workflows

Languages: Go, Ruby, Bash, Python, TypeScript