Building Ethics Compliance Into Your AI Pipeline
Integrating fairness checks and bias audits into a production ML pipeline reduced bias-related incidents by 82% and added only 14 minutes to the training cycle.
Portfolio
Systems built, documented, and reflected upon.
Integrating fairness checks and bias audits into a production ML pipeline reduced bias-related incidents by 82% and added only 14 minutes to the training cycle.
8 of 11 knowledge bases failed within 6 months. The 3 survivors embedded knowledge creation into existing workflows instead of adding separate systems.
Query pattern optimization across 3 Snowflake deployments reduced annual costs from $412,000 to $187,000 without changing business logic or removing features.
Migrating 47 DAGs to Airflow 3.0 event-driven scheduling reduced median latency by 62% and eliminated 340 idle runs per week.
A 14-engineer team cut cloud costs 41% by replacing Netflix-inspired architecture with patterns designed for their actual scale of 340,000 monthly orders.
Golden path pipelines make secure deployment the default. Vulnerabilities escaping to production dropped from 12 to 1 per quarter while deployments increased 28%.
WordPress configured as headless infrastructure meets enterprise requirements at 57% lower cost than bespoke systems. Here is the architecture that proves it.
An evaluation pipeline designed as durable infrastructure caught 23 regressions and reduced model migration from 6 weeks to 9 days across 4 model transitions.
A hybrid inference architecture routing between local and cloud models cut costs 67% while eliminating data sovereignty concerns for 45,000 daily healthcare queries.
Redesigning RAG as foundational data infrastructure reduced per-query costs 75% and improved answer accuracy from 67% to 91% across 2.3 million monthly queries.