work

selected systems

AI evals

Evaluation infrastructure for Spaces

Brex, 2026

Built evaluation infrastructure for Spaces, Brex's AI financial analyst, including a 200+ scenario suite covering SQL correctness, chart generation, insight quality, and output formatting. The system combines deterministic checks, narrowly scoped LLM judges, and trace review so product iteration does not outrun measurement.

How I think about eval systems

Semantic layers

Semantic layer and AI infrastructure for Spaces

Brex, 2025–2026

Worked on the semantic engine and agent infrastructure behind Spaces: translating warehouse data into business-facing concepts, enforcing safer access patterns, and exposing financial reporting workflows across Brex's product surface, MCP infrastructure, and various external integrations.

Why the semantic layer is execution infrastructure · Brex journal · Cube case study

Metadata and provenance

Metadata catalog evaluation framework

Brex, 2025

Developed an evaluation framework for metadata catalog tooling across discoverability, lineage, and governance. The goal was to ground platform build-vs-buy decisions in real access patterns and technical-user workflows instead of vendor demos.

How I think about data catalogs

Streaming systems

Zero-downtime versioning for Flink

Brex, 2025

Designed deployment and versioning workflows for stateful Flink pipelines, with concurrent job promotion, canary outputs, and rollback paths for migrations where failed restores could mean multi-day backfills.

Upgrading Flink without downtime

Data platforms

Mortgage data platform behind Credit Karma Home Loans

Credit Karma, 2021–2024

Architected and led a Kafka-based mortgage application monitoring platform for visibility after partner handoff. It became a core system behind Credit Karma Home Loans and later shaped a broader platform pattern for loan lifecycle analytics.

Credit Karma Home Loans

talks

How Brex Built AI-Native Financial Reporting

Agentic Analytics Summit (Cube) · 2026

How we built Spaces, Brex's embedded AI financial analyst, on a semantic layer, and what it takes to make an LLM agent answer real financial questions correctly: the ontology, certified queries, and the evaluation infrastructure that keeps it honest.

Watch the recording →

open source