42 lines
4.1 KiB
Plaintext
42 lines
4.1 KiB
Plaintext
# Indiana Holmes
|
|
|
|
Seattle, WA | 425-280-0023 | indianaholmes1@icloud.com
|
|
|
|
## Technical Profile
|
|
|
|
Independent systems engineer specializing in homelab architecture, AI automation systems, cybersecurity-focused infrastructure, embedded device engineering, and scalable self-hosted platforms. Experienced operating Proxmox virtualization clusters, Linux infrastructure, AI orchestration systems, RF communication platforms, telemetry hardware, and production-style service environments. Strong hands-on background combining systems engineering, infrastructure operations, automation pipelines, API integrations, advanced AI workflows, custom MCP development, local LLM infrastructure, and distributed services from concept through deployment.
|
|
|
|
## Core Engineering Expertise
|
|
|
|
- Proxmox virtualization clusters, VM / CT orchestration, Linux administration
|
|
- AI infrastructure, local LLM deployment, inference pipelines, and AI acceleration
|
|
- Advanced AI workflows, agent systems, custom MCP integrations, and API orchestration
|
|
- Cybersecurity-focused infrastructure hardening, segmentation, and remote access design
|
|
- Docker containers, automation systems, and self-hosted SaaS platforms
|
|
- Embedded firmware engineering across ESP32 device families
|
|
- RF systems including LoRa, Meshtastic, and CC1101 wireless experimentation
|
|
- Infrastructure monitoring, diagnostics, troubleshooting, and operations
|
|
|
|
## Major Systems & Projects
|
|
|
|
- Designed and operate a multi-node homelab infrastructure hosting AI services, automation platforms, databases, development environments, and websites using Proxmox hypervisors and Linux containers.
|
|
- Built advanced AI automation systems integrating local LLMs, APIs, orchestration logic, custom MCP tooling, and distributed workflows for infrastructure operations and research.
|
|
- Engineered ESP32-based telemetry devices, wireless monitoring systems, custom firmware platforms, and RF communication systems for connected hardware applications.
|
|
- Developed long-range RF and mesh networking projects using LoRa radios, Meshtastic networking, CC1101 modules, and distributed sensing platforms.
|
|
- Implemented secure network infrastructure including SSH administration, VPN tunnels, segmentation strategies, reverse proxy routing, secure service exposure, and infrastructure diagnostics.
|
|
|
|
## Infrastructure Engineering & Operations
|
|
|
|
- Developed infrastructure automation workflows using Linux tooling, Bash, Python, Node.js, APIs, and containerized services to simplify deployment, monitoring, and operational management.
|
|
- Architected and maintained self-hosted SaaS ecosystems spanning Git services, automation platforms, cloud storage, AI infrastructure, telemetry systems, and development tooling.
|
|
- Experienced troubleshooting complex multi-system environments involving networking, virtualization, containers, AI infrastructure, embedded systems, Linux administration, and distributed services.
|
|
- Built scalable development and infrastructure environments integrating databases, AI inference stacks, automation services, monitoring systems, and secure remote access tooling.
|
|
|
|
## Technologies & Platforms
|
|
|
|
Linux • Proxmox • Docker • Virtualization • Python • Bash • Node.js • REST APIs • Git • ESP32 • Arduino • Firmware Development • LoRa • Meshtastic • AI / LLM Infrastructure • Advanced AI Workflows • Agentic AI Systems • MCP Development • API Integrations • Automation Pipelines • n8n • Self-Hosted Services • Networking • SSH • VPN • Reverse Proxies • Cybersecurity • Infrastructure Hardening • Linux Networking • Infrastructure Monitoring • Cloudflare Tunnels • GitLab • Gitea • MongoDB • Redis • RF Communications • Automation Engineering • Homelab Architecture • Service Orchestration
|
|
|
|
## Professional Focus
|
|
|
|
Seeking an engineering and infrastructure-focused role where strong hands-on experience with systems administration, infrastructure operations, automation engineering, AI tooling, cybersecurity-oriented networking, and scalable technical problem solving can contribute to large-scale operational reliability and technical innovation.
|