Charles C. Taylor

Software Development Team Manager , AWS data-center capacity planning

I build capacity-planning software for data-center decisions—and lead the teams that run it.

17+ years in data-center infrastructure and operations, most recently in capacity engineering, production platforms and applied AI.

Selected outcomes

  • 8 or more people of planner and engineer work automated every year

    Headcount equivalent of automation my team and I built

  • 375k Amazon-ians used a platform I created or managed. approximately 2,500 monthly users

    AWS capacity-planning and S&OP platform

  • 30 percent shorter planning cycles

    Planning-cycle duration

Context for these figures

Platforms built directly or with my team

Built several business-critical platforms end to end, some myself and some with my team, replacing manual processes and offline files with automation

Selected work

Systems I built, redesigned and lead

Top-down fantasy town: timber-framed shops labelled Weapons, Armor, Items and Inn line a cobbled road, with a white cathedral on the right, pink blossom trees, and small characters walking.
A town in Dungeons & AI, captured from the game engine.

Personal project · not affiliated with AWS

Building a game with a team of AI coding agents

Dungeons & AI is a browser role-playing game I built as a personal project in 2026, with AI coding agents writing the code. The engineering problem was keeping many agents from breaking one codebase. I designed a task board, file claims and a test-gated merge queue that made parallel AI work safe to land.

My role: I designed the workflow, set the direction and priorities, answered the agents' design questions, and ran every release. All of the code was written through AI coding agents that I directed; my son helped a little along the way.

  • More than 4,000 changes landed in about two months (Aug–Oct 2026).

AWS

Applied AI for engineering and planning workflows

I conceived my team's first AI product: a planning assistant whose agents explain variances, run investigations and check cycle readiness. We built its knowledge base first, from the logic behind the team's dashboards, so the agents answer from real planning rules. Separately, I lead an AI initiative to reduce manual work in code deployment.

My role: Conceived the assistant; leading the deployment initiative

  • My v1 cut 9 hours from a 14-hour process by eliminating redundant data calls, which I found using AI, turning a once-a-week run into several runs a day
  • Piloted an AI method to capture the metadata of 3,000+ dashboards, so the team's chatbot answers “where do I get data for X?” and pulls the real data

Unofficial internal initiative

Helping employees discover internal opportunities

As an unofficial side project, I built and ran an internal tool that made it easier for employees to explore opportunities inside the company. People installed a small client script, and it called a set of APIs I hosted to show them richer organizational information than they could otherwise see.

My role: Built and operated

Leadership

Building systems. Building teams.

I lead a team of 10 engineers that owns the capacity-planning and S&OP platform behind AWS data-center planning. Most of that work is turning spreadsheet reports, planning logic and organizational knowledge into self-service systems, then keeping those systems reliable.

Product discovery
I replaced ticket-based intake with direct engagement between our engineers and the customers who use our tools.
Rapid prototyping
We ship weekly, and customers build AI-assisted prototypes alongside the team.
Architectural direction
I set the architecture direction for systems built on Python, AWS Lambda, S3, Redshift, OpenSearch, ETL and APIs, and define the performance requirements critical planning tools must meet.
Production operations
I own them end to end: a weekly on-call escalation rotation, operational health reviews, quarterly roadmaps and annual planning.
Team development
I hire and develop engineers across systems, software, frontend and UX, including senior SDEs.

See how the capacity platform was built and run

About

From physical infrastructure to intelligent infrastructure

I got my start in data centers in 2005 in site services, leading a team of technicians who supported data center IT operations, and I used SQL to automate the labels the team produced by hand. In 2011 I came back to data centers as a network engineer, deploying core routers and switches. At Microsoft I moved into capacity: deployment processes, rack and server placement, then forecasts and JavaScript tools on SQL and REST APIs. At AWS I built a regional capacity-planning and simulation tool myself, then the data foundation underneath capacity planning. Since 2022 I have led the team that runs the planning platform, and I am bringing applied AI into how we plan and ship.

Technical breadth

CAPACITY & PLANNING
  • Demand/supply forecasting (0–2 and 5-year horizons)
  • S&OP
  • utilization
  • allocation
  • deployment and infrastructure investment
PLATFORMS & RELIABILITY
  • Python
  • SQL
  • AWS Lambda/Glue/S3/Redshift/EC2
  • PostgreSQL
  • OpenSearch
  • DuckDB
  • ETL
  • REST APIs
  • Tableau Server
  • monitoring
  • high availability/disaster recovery
APPLIED AI & LEADERSHIP
  • Multi-agent multi-vendor orchestration
  • Retrieval Augmented Generation (RAG)
  • natural-language and voice interfaces
  • architecture reviews
  • roadmaps
  • hiring and senior-engineer development

Career

  1. Microsoft

    1. Data Center Site Services –
    2. Senior Network Engineer –
    3. Regional IT Program Manager –
    4. IT Program Manager / Developer –
  2. T-Mobile

    1. Technical Project Manager –
  3. Amazon Web Services (AWS)

    1. Capacity Planner / Developer –
    2. Senior Data Engineer –
    3. Software Development Team Manager – Present

Full roles, education and detail in my resume

Contact

Let’s talk about complex systems, capable teams, and what comes next.