Edward Q. Earley

Leading a 16-engineer team building the capacity governance platform for Meta’s ad-serving infrastructure — the system that controls how resources are allocated, enforced, and reclaimed across dozens of services. My role spans platform engineering, people leadership, and AI-native transformation of both our infrastructure operations and how we run the team itself.

• Designing and shipping automation that replaced manual resource management with a self-service platform — provisioning, quota enforcement, cost attribution, and anomaly detection at a scale that supports billions in annual ad revenue.
• Introducing AI agents into infrastructure operations — building systems that detect cost anomalies and recommend optimization actions, replacing manual engineering analysis with automated workflows.
• Driving an AI-native transformation of engineering management itself — using AI to automate program tracking, status reporting, team communications, stakeholder management, and decision support across a 16-person organization.
• Driving tens of millions in annual infrastructure cost savings through platform automation and AI-accelerated optimization.
• Building and organizing three engineering pods from an inherited flat structure, each with clear ownership: resource optimization, fleet observability, and enforcement.
• Growing the team from 10 to 16 engineers in two quarters through active sourcing, sell calls, and onboarding. Managing the full people lifecycle — hiring, performance calibration, growth planning, and career development for engineers spanning IC3 through IC6.
• Full-stack product + engineering ownership — owning problem framing, roadmap trade-offs, and execution priorities directly.

Team Size: 16 engineers
Scale: ~$30M+ in annual infrastructure cost savings

Led a ~30-person org (3 managers, 6+ senior ICs) across JVM platform, big data, DevOps tooling, and codebase management.

• Rebooted hiring by making engineering managers directly accountable for outcomes; onboarded 7 engineers in <2 months across 2 continents.
• Built the JVM Platform team from 1 engineer to a 10-person EU/US-distributed org supporting 300+ Tier 1 and Tier 2 services.
• Stood up a 3-person Apache Flink team for event-based services; shipped into production across multiple Tier 1 services.
• Introduced OKR reporting and MBRs with delivery metrics used at exec level; format replicated at parent org.
• Created a Single-Threaded Ownership program to develop future leaders; 2 engineers fast-tracked for promotion, model adopted at parent org.

Team Size: ~30 reports (3 managers, 6+ senior ICs)
Scale: Wayfair revenue ~$14B, market cap ~$30B (2021)

High-performance incubator team within S3’s Control Plane — 4 concurrent workstreams at planetary scale.

• Citadel: shipped S3’s first worldwide real-time hardware failure reporting engine — baseline technology for ML and predictive analytics on global S3 fleets.
• Mechanic: tiger team that eliminated the need for SSH access to production; reduced SSH by 90%+ in four months.
• ONAC: infra-as-code migration of S3 to native AWS networking — the foundational network architecture and security model for S3.

Team Size: 5 engineers
Scale: Operated within S3 (est. ARR ~$10B+) — stabilized planetary-scale Control Plane services; 90%+ SSH elimination

Member of the executive team. Hybrid IC-executive role leading a full-company transformation to data and platform technologies at a Chicago edtech company.

• Delivered the first-generation Data Analytics Platform on time and on budget with a brand-new team in 5 months.
• Restructured all of Product Development into cross-functional squads in the first weeks; doubled engineering headcount in 6 weeks without a recruiter.
• Reset Agile and QA practices and put modern DevOps tooling and monitoring in place — all within the first 2 months.
• As IC: built a GitOps-based Kubernetes platform with CI/CD (Codefresh, Flux, EKS) and migrated environments to new AWS accounts via Terraform.
• Led Otus to 12th Best Small Company to Work For in Chicago (Built In Chicago, 2019).

Team Size: 25+ reports — member of the executive team, co-owned engineering with CTO across QA, engineering, and program management
Scale: Transformed a seed-stage engineering org into a product development machine in under 6 months

Member of the executive team. Two-year organizational transformation of a B2C parking marketplace — rebuilt engineering from the ground up.

• Owned a 2-year transformation plan across process, people, architecture, and culture — delivered on time and on budget.
• Scaled platform from an early-stage marketplace to enterprise-ready infrastructure supporting national expansion: 100x increase in technical delivery capacity, 10,000x growth in transactional throughput.
• Defined and built a modern platform (Java, Kubernetes, Kafka); stood up a net-new Shared Services division — Data, Search, Developer Tools, and APIs teams.
• Introduced a pure managed-services DevOps model; deliberately avoided the anti-pattern of a centralized DevOps team by empowering product squads to own their infrastructure (Conway’s Law).
• Rebooted QA; introduced lightweight Agile with normalized delivery metrics; served as engineering lead on a tuck-in acquisition (2017).
• Doubled engineering headcount without a dedicated recruiter; built management tier and senior IC layer; created and hit first engineering budget.

Team Size: 75+ — all engineering functions, top to bottom
Scale: Platform transformation that enabled national expansion; SpotHero acquired by Uber (valued ~$500M at Series D)

Technical director across Data Engineering, API Gateway, Security Engineering, DevOps, and Streaming Data at a Chicago industrial IoT startup.

Team Size: 35+ staff
Scale: $2B-valued industrial IoT unicorn (Caterpillar-backed)

Member of the executive team. Walked in as a software engineer; walked out as CTO — 7-year progression through Platform Engineering to executive leadership.

• Built award-winning platforms (Players Life, Play4Fun Network/SG Universe) that created the US B2B social casino category; platform grew to ~$30M annual revenue.
• Architected a cloud-native AWS platform in Python as a low-end B2B disruptor — defined a product category that didn’t exist, built with a 5-person team.
• Solely designed and implemented a Java web services platform connected to 1,000+ slot machines — with a fully automated integration test framework; architecture predicted features later found in Dropwizard and Spring Boot.
• Re-architected a heavily distributed, debt-laden platform using PaaS, microservices, and the Strangler pattern; restructured the org to mirror the architecture (Conway’s Law).
• Executed a hard reboot of a broken global technology organization: doubled revenue and halved operating costs in year one through architectural reform and DevOps/CI/CD transformation.

Team Size: 100+ worldwide
Scale: WMS Industries acquired by Scientific Games for ~$1.5B (2013); Scientific Games market cap ~$7B at peak