I build platforms that stay reliable when the numbers get uncomfortable.

Modernized model serving for hundreds of millions of daily search queries while improving isolation, latency, and availability.

Context

Single-tenant search clusters limited resource efficiency and made consistent multi-locale operation harder.

Decision

Designed secure multi-tenant Kubernetes model serving with multi-tier inference routing and shared query normalization.

Scale

Hundreds of millions of daily queries across multi-tenant, multi-locale production environments.

Outcome

99.9% availability and 25% lower inference latency, with architecture patterns adopted across Search teams.

Built the reporting and analytics foundation used for fraud detection and chargeback analysis across a high-volume payments environment.

Context

Risk teams needed faster, more reliable access to transaction data across reporting, analytics, and operational workflows.

Decision

Engineered a GCP reporting platform, introduced Databricks analytics, migrated core workflows to DynamoDB, and modernized the data layer.

Scale

More than 10 million daily transactions supporting fraud detection and chargeback analytics.

Outcome

30% analytics efficiency gain, 30% lower data cost, and a 50% faster feature-to-production lifecycle.

Turned subscription creation, access control, and cloud billing into a governed self-service platform for engineering teams.

Context

Cloud subscription and budget workflows were too manual to support a large engineering organization consistently.

Decision

Architected the Azure Right-to-Provision service, TypeScript RBAC, automated billing, and the Cloud Portal 2.0 developer experience.

Scale

Automated cloud access and budget management for more than 5,000 engineers.

Outcome

A governed self-service path to cloud resources, supported by a Kafka-based observability system that reduced incident detection time.

Led monitoring, alerting, and logging systems supporting a large global cloud footprint and strict incident response expectations.

Context

Infrastructure teams needed consistent monitoring and fast escalation across a globally distributed production environment.

Decision

Led monitoring across Icinga, Grafana, and PagerDuty, and built a Logstash, Kafka, Elasticsearch, and Kibana logging pipeline.

Scale

50+ data centers, 10,000 servers, and 500 TB/day of log data.

Outcome

99.99% uptime and analysis that informed more than $3M in infrastructure cost reductions.