Senior Network Automation Engineer · Platform & DevOps
15+ years in telecom and 12+ in network engineering, now focused on network automation, platform engineering, and infrastructure software. I build the Python and Go services, Kubernetes platforms, and CI/CD pipelines that let large service-provider networks be changed safely, at scale.
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Open to remote and Oklahoma City-area roles
A high-level overview of a few projects I've worked on at Cox Communications. I'm happy to go into more detail in conversation.
Internal platform aggregating topology, inventory, telemetry, and service data for 70,000+ network elements, used by 1,000+ employees. Python and Go microservices on Kubernetes, with dashboards, Redis caching, and Prometheus/Grafana monitoring.
Daily use of AI coding agents for development, review, testing, and documentation, plus controlled tooling that gives agents structured platform context while blocking direct production-device access.
A Python bootstrap that devices fetch over DHCP/HTTP, detect their own platform, pick the right software, and upgrade themselves across Juniper, Cisco, and Arista. Paired with a service that resolves the correct production config from a serial number. Used on 1,000+ turn-ups.
Staged Ansible/AWX workflows for 700+ IOS XR routers plus Nexus, Arista, and Juniper, with routing and service verification and failure gates. Raised safe concurrency from 2–4 devices to 10–20.
Built a Python-based Ansible dynamic inventory plugin that syncs production routers from an internal discovery API into AWX. It became the shared inventory for pre/post validation, software upgrades, technical bulletins, and other network automation workflows, and remains actively maintained in production today.
Replaced manual Segment Routing deployments with staged workflows that validate the underlay before traffic activation. Automated streaming-telemetry deployment and per-device certificate rotation across four vendors.
Sample networks from small to large, shown in the topology view of the network engineering platform. I developed a layout that puts the P routers in the center and fans the PE routers out around them, so the structure of a network is easy to read at a glance.
I started in technical support and field operations, moved into service-provider network engineering, and gradually turned the repetitive parts of that work into software.
Apr 2024 – Present
Cox Communications · Platform Engineering / DevOps / Network Automation
Build and support the internal network engineering platform. Python and Go services, Kubernetes, GitOps with Jenkins and ArgoCD, and shared production ownership of what the team ships.
Oct 2019 – Apr 2024
Cox Communications
Technical lead on a team chartered to stand up ZTP that grew into provisioning, validation, and upgrade automation. Led weekly progress reviews, divided quarterly work across engineers, and mentored network engineers new to Python, Ansible, and software practices.
Apr 2014 – Oct 2019
Cox Communications
Production engineering across seven markets and 80+ hub sites. Led regional modernization, including the move from Cisco 7600s to ASR 9000, planning and leading maintenance windows, authoring MOPs, and coordinating change bridges, plus escalations and on-call.
2010 – 2014
Cox Communications
Started in inbound technical support and moved up to technical support lead. Then went into the field as a service assurance technician, gaining hands-on experience with equipment turn-ups and troubleshooting, including racking and cabling, fiber patching, and work in data centers and hub sites.
Beyond my day job, I design, build, and operate my own software and infrastructure, from production farm systems to networking and game-server projects. Some of the farm application code is private, but I'm glad to walk through the architecture, engineering decisions, and operational approach in an interview.
A multi-cluster Kubernetes environment I designed and run end to end. ArgoCD is the source of truth for everything deployed; Kargo promotes first-party app images from dev to prod; Renovate keeps charts and third-party images current. Secrets are encrypted in Git with sops/age and decrypted in-cluster. A WireGuard mesh links the nodes so internal services never touch the public internet. Includes Prometheus/Grafana monitoring, SSO, S3-compatible object storage, Ansible-based node bootstrap, and documented backup and disaster-recovery procedures.
Every change goes through pipelines I built: Gitea Actions builds an image per push, each pull request gets its own preview environment, and Kargo promotes release images from dev to prod, with Renovate keeping dependencies current. The same pattern ships the farm app, the website, the game server, and the server list.
A FastAPI and MongoDB web app for livestock, pastures, hay inventory and sales, fields, and equipment, with a retail store (Square payments) and an LLM-assisted equipment troubleshooting agent. I built the foundation: the data model, modular routes, role-based access control, API tokens, a CLI, and a test suite. We've grown it together with my farm partner, who was new to software development when we started and whom I mentored along the way.
The farm's public Flask site, with product pages, a contact form, a live Facebook feed, and QR-code landing pages for printed campaigns. The /shop storefront is a thin server-rendered client of the farm app's key-authenticated API, so pricing and inventory logic live in one place and the API key never reaches the browser.
A Return to Castle Wolfenstein mod and community server, written mostly in C. The game client is compiled to WebAssembly, so anyone can play in the browser with nothing to install; browsers can't send raw UDP, so the client reaches the server through a UDP-over-WebSocket bridge. Native players get a one-command install for Linux and Windows. The site adds live server status, a live-watch view, and game history. Runs on Kubernetes through the GitOps platform above.
A Go reimplementation of the Quake 3-style master server, which game servers register with so players can find them. It backs a public RTCW / ET server list that tracks online servers, player counts, mods, and master uptime over time. Deployed through the same GitOps pipeline.
The farm app keeps dated weights and events for every animal, plus hay inventory and equipment hours, so decisions start from the record instead of memory. Its litter comparison lines up to six litters by days since farrow and compares survivors, mortality, average daily gain, 56-day weight, and days to 50 lb, replacing "that litter seemed good" with numbers when choosing which pairings to repeat and which animals to keep. Weight alerts flag animals falling behind, and a maintenance dashboard shows equipment that is down or overdue.
The screenshots use fictional demo data. In it, the same boar sires both the slowest and the fastest litter, the kind of result memory misses.
Less More · From my self-hosted Git server, where this work lives.
This portfolio is deployed the same way as the apps above: a git push becomes a container image, a promotion, and a rollout to Kubernetes, with one deliberate manual gate before production.
Every change starts as a PR, and every PR gets its own environment.
Merging promotes the same image through staging to production, with a person in the loop before prod.
v26.10.01-ab12cd34I'm interested in network automation, platform engineering, DevOps, and infrastructure roles where deep networking experience meets software.
travissandmann@gmail.com Résumé (PDF) LinkedIn GitHub Cover letter (PDF)