Engineering work ledger
Case studies
Three production systems, recorded as problem, intervention, operating evidence, and outcome.
Outcomes from full-time engineering roles, not consulting clients.
01 · Ford Motor Company · Lead Engineer
Eliminating a 30-Day Manual Process
Open caseClose caseApprox. $5MAnnual Savings
01 · Ford Motor Company · Lead Engineer
Eliminating a 30-Day Manual Process
Open caseClose caseThe Problem
Ford Credit was spending millions on slow, manual vehicle audits. Auditors drove hundreds of miles to physically count cars at dealerships, discovering discrepancies weeks after the financial impact. In a rising interest rate environment, this lag was expensive.
What We Built
An IoT telemetry platform that automated verification for 450,000+ vehicles, saving around $5 million annually in operational costs and interest rate carry. What used to take weeks now happens in real-time.
How It Works
I led the architecture of a high-scale event-driven system using Kafka, Google Cloud Pub/Sub, and Azure IoT Hub. The system ingests 600,000+ vehicle events daily with state management to ensure data integrity in a distributed environment. Handles out-of-order events through Kafka partitioning by vehicle_id and stateful buffering.
Evidence basis: Full-time Ford role · production platform · internal operational and finance measures · public implementation unavailable
Transferable lesson: Whether your team is 5 or 500, the pattern is the same — find the manual bottleneck, automate it, measure the savings.
Systems: Kafka · Google Cloud Pub/Sub · Azure IoT Hub · Event-Driven Architecture · IoT Telemetry
02 · Morningstar · Lead Engineer
Cutting 20% of Weekly Engineering Bandwidth
Open caseClose case10hWeekly Engineering Time Reclaimed
02 · Morningstar · Lead Engineer
Cutting 20% of Weekly Engineering Bandwidth
Open caseClose caseThe Problem
Every morning started the same way. An engineer clicking through 80 Postman requests to trigger compliance checks. One by one, like a human cron job. This ate up 20% of our team's weekly bandwidth. When someone got sick for a week, compliance checks just... stopped. That's when we knew we had to automate.
What We Built
I transformed the architecture to fully event-driven, freeing up 10 engineering hours every week. This let us onboard 7 new enterprise recordkeepers with zero added overhead while improving throughput and reducing latency by 35%.
How It Works
I implemented load-aware scheduling that monitors database capacity before kicking off new jobs via AWS SQS and ephemeral Fargate tasks. Instead of blindly running all checks daily, the system uses database diffing to detect meaningful changes and only publishes events when there's actually a delta. Smart resource utilization that scales.
Evidence basis: Full-time Morningstar role · production compliance system · internal delivery and performance measures · public implementation unavailable
Transferable lesson: Manual processes that 'only take 20% of someone's time' add up fast. Automate them, and suddenly your team can innovate instead of maintain.
Systems: AWS SQS · AWS Fargate · AWS Lambda · Event-Driven Architecture · Database Optimization
03 · Ford Motor Company · Lead Engineer
Protecting America's Most Stolen Vehicle
Open caseClose case2024Production Launch
03 · Ford Motor Company · Lead Engineer
Protecting America's Most Stolen Vehicle
Open caseClose caseThe Problem
The Ford F-150 is America's best-selling truck. Also its most stolen. Owners needed real-time protection, but tracking vehicles raises serious privacy concerns. We had to balance theft recovery capability with strict data privacy compliance.
What We Built
A privacy-first telemetry system now deployed in thousands of 2024 F-150s, providing owners with cloud-backed theft recovery. When a theft is reported, the system automatically increases tracking frequency to help police recover the vehicle faster.
How It Works
I architected a Zero Trust ingestion layer using GCP Pub/Sub and Kafka where all telemetry is anonymized at entry, with PII encrypted in a secure vault accessible only via ephemeral tokens during active recovery. The adaptive recovery mode transitions the vehicle's modem to high-frequency reporting when theft is detected, balancing recovery speed with cellular costs and battery drain.
Evidence basis: Full-time Ford role · production vehicle program · internal launch record · public implementation unavailable
Transferable lesson: Security and privacy don't have to be trade-offs. With the right architecture, you can have both — and ship a product customers trust.
Systems: GCP Pub/Sub · Kafka · Zero Trust Architecture · Privacy-First Design · IoT
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