Charles C. Taylor
Software Development Team Manager · AWS data-center capacity planning
Last updated
Notable AWS capacity-planning impact
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375k Amazon-ians used a platform I created or managed. ~2,500 monthly users
MONTHLY PLATFORM USERS:
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30% shorter planning cycles
SHORTER PLANNING CYCLES:
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$60M–$120M in annual savings, enabled by delivering data centers when they're needed and getting more from existing infrastructure
ANNUAL SAVINGS ENABLED:¹
Enabled by delivering data centers when they're needed and getting more from existing infrastructure; see AWS experience below.
Profile
Hands-on engineering leader with 17+ years in data center infrastructure and operations across AWS and Microsoft. Built systems as a capacity planner and data/software engineer; now leads the platforms team behind large-scale data center planning. Combines architecture, production ownership, customer-led delivery and AI-assisted engineering.
Professional experience
Amazon Web Services (AWS), Seattle, WA
Software Development Team Manager
to Present
- PLATFORM OWNERSHIP: Own the capacity-planning and S&OP platform for AWS data center planning, serving ~2,500 monthly users; set the architecture direction for its data pipelines, ETL, APIs, OpenSearch and planning tools.
- PLANNING IMPACT: Automated planning logic and offline files into self-service systems, cutting planning cycles 30%; they help AWS deliver data centers when they're needed and get more from existing infrastructure, enabling $60M–$120M in annual savings.
- PERFORMANCE & RELIABILITY: Set a sub-3-second page-load requirement for 40 GB+ demand plans and contributed to the OpenSearch/DuckDB backend design; cut critical dashboard refresh from 8+ hours to 40 minutes or less, with zero failures across 7 consecutive cycles.
- ENTERPRISE SCALE: Scaled Tableau Server from one node to a five-node cluster; grew from ~200 to ~9.5K quarterly users and 3,000+ dashboards, ended peak-hour access failures, and saved $2.5M+ over 3 years through automated license reclamation.
- AI KNOWLEDGE BASE: Piloted an AI method to capture the metadata of 3,000+ dashboards from a small sample, then handed the bulk capture to an intern; in the team knowledge base, a chatbot answers “where do I get data for X?” and pulls the real data. The same catalog later guided rebuilding Tableau dashboards on pipelines from source to OpenSearch, with APIs serving them.
- AGENT ORCHESTRATION: Built an orchestration engine coordinating 40+ AI agents. It delivers page content with minimal SDE time, improves with each iteration, and merges 350+ changes a day into tested canary environments behind feature flags that engineers or business owners control, so deploying needs no code. It also runs text- and voice-enabled monitoring that resolves tickets and self-heals, and is the authoritative knowledge base for the org’s software and systems.
- DELIVERY MODEL: Replaced ticket-based intake with direct engineer–customer engagement, weekly shipping and customer-built AI-assisted prototypes; 5 engineers delivered 40 capabilities in 8 months.
- DEPLOYMENT AUTOMATION: Lead development of an AI orchestrator that identifies service flaws and reduces manual code-deployment work; annual cost reduced from $2.5M to $1.4M to date; 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.
- PEOPLE & OPERATIONS: Lead 10 systems, software, frontend and UX engineers, including Senior SDEs; hired 18 and promoted 7, with average team tenure of 3.3 years vs. Amazon's 1.5-year average. Own weekly on-call escalation, WBR/MBR health reviews, quarterly roadmaps and annual operating planning.
Senior Data Engineer
to
- DATA FOUNDATION: Built AWS capacity-planning data pipelines from multiple infrastructure and planning sources using Python, Lambda, ETL, S3, databases and data lakes; the database served ~90K users monthly.
- MONITORING SERVICE: Built the first version of a monitoring and alerting service (frontend and APIs) in under 2 months after a year of scoping; it now runs 1,500+ SQL alarms and automates 100K+ tickets monthly, saving 3–8 people's worth of manual work.
- INGESTION REDESIGN: Reduced demand-data ingestion from 3 hours to under 10 minutes by replacing the architecture with an in-memory pipeline and partitioned data domains rather than tuning the old system.
Capacity Planner / Developer
to
- HANDS-ON SYSTEM BUILD: Personally built infrastructure, database, APIs and UI for a regional data center capacity-planning and simulation tool; planners fully adopted it within 3 months, replacing offline tracking files.
- LONG-RANGE FORECASTING: Produced five-year regional and AZ-level data center forecasts in SQL, Redshift, Python and Tableau; surfaced fleet capacity shortfalls and presented recommendations to senior leadership.
Earlier experience & selected work
Microsoft, Chicago, IL / Redmond, WA
IT Program Manager / Developer
to
- CAPACITY TOOLS: Built JavaScript applications on SQL and REST APIs; generated 0–2 year data center capacity forecasts from multiple sources and customer input to guide deployments.
Regional IT Program Manager
to
- DEPLOYMENT OPERATIONS: Designed server deployment and troubleshooting processes and technician metrics; partnered with capacity planners to improve rack and server placement.
Senior Network Engineer
to
- NETWORK INFRASTRUCTURE: Designed and deployed core routers and aggregation/top-of-rack switching in public and government (ITAR) data centers; automated configurations to speed delivery and reduce errors.
Data Center Site Services
to
- TEAM LEAD: Built a SQL-based process that generates labels, saving hundreds of hours each month; led a team of technicians supporting data center IT operations.
T-Mobile, Bothell, WA
Technical Project Manager
to
- IT PM: Deployed retail IT infrastructure and built database tooling for deployment operations.
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.
Selected engineering projects
Project Factorum
Unofficial internal project
Built and operated an internal opportunity-discovery product used by 370K+ unique employees (peak ~90K monthly); installed client script backed by ~25 hosted APIs on Python, Aurora and ECS.
AI-Built Game
Personal project · 2026
Publicly launched a 160K+ line application (Azure, JavaScript, Phaser, Python) built with AI coding agents coordinated through a custom task-and-merge system.
Education
- Master of Business Administration (MBA), University of Phoenix
- Computer Science Minor, University of Phoenix
- Associate Degree, Computer Science & Networking, ITT Technical Institute