SWE @ Ford

currently working as a software engineer at ford motor company in toronto, building backend infrastructure and automation systems for critical order processing workflows in automotive manufacturing. my work focuses on designing scalable distributed systems, implementing observability tooling, and eliminating manual processes through intelligent automation.

one of my primary contributions has been designing and implementing automated validation and persistence pipelines for order ingestion. i architected end-to-end pipelines that validate incoming orders against business rules, handle edge cases, and persist data to downstream services without human oversight. this eliminated manual order ingestion paths and reduced human intervention by over 60%, significantly improving throughput and reducing processing errors. the pipeline includes comprehensive validation logic, intelligent retry strategies with exponential backoff, and dead letter queues for orders requiring manual review.

i instrumented distributed services across the order processing stack with datadog apm, implementing distributed tracing, custom metrics, and proactive alerting. this gives our team real-time visibility into service health, request latencies, and error rates across microservices. with distributed tracing, we can track individual orders through the entire pipeline, pinpointing bottlenecks and failures with precision. the custom dashboards and alerting system i built have drastically reduced mean time to detection and resolution for incidents, enabling low-latency debugging and proactive performance regression detection.

working with technologies like java spring boot, kafka for event streaming, postgresql for persistence, and kubernetes for orchestration has given me deep exposure to enterprise-grade distributed systems architecture. this role has been an incredible learning experience in large-scale systems, modern observability practices, and the complexities of automotive software engineering.