AI observability and evaluation platform for enterprise ML teams.

• Designed and built a large-scale Go autonomous agent platform (1,860+ MCP tool APIs across

72 modules) with sandboxed execution environments, state checkpointing, fault recovery, and

trust-boundary isolation – recognized at All-Hands as "most complex agent built at Galileo."

• Served as Incident Lead for 4 P0 production incidents (6,200+ stuck jobs, Redis

misconfigurations across 3 clusters, production API outages), resolving all within 24 hours

with documented root causes and permanent fixes.

• Implemented agent execution infrastructure and auth frameworks – OAuth-based RBAC across 17

customer environments, tiered trust boundaries, rate limiting and circuit breakers for 15+

external integrations, and OpenTelemetry metrics with 12 Grafana dashboards.

• Built a durable execution engine with 5-minute checkpointing, atomic state writes,

fault-tolerant consensus, and batch API optimization (50% cost reduction, 90% prompt cache

hit rate) – enabling 24-hour autonomous execution cycles with crash recovery across 23

concurrent agent workers.

• Led enterprise customer migration from v1 to v2 with a Go data-migration CLI,

ClickHouse/Postgres backup-restore, DNS cutover automation, and Grafana tracking – zero data

loss, zero unplanned downtime.

• Managed deployments for 17 enterprise customers including Fortune 20 and Fortune 50

companies across AWS, GCP, and Azure, driving CVE remediation, GPU model bundle

configuration, and TLS 1.3 hardening.

AI platform for NLP and document understanding, serving defense and intelligence customers.

• Automated ML workflow deployments using GitHub Actions, transitioning 12+ production ML

deliverables from manual Kubernetes deployments to ArgoCD automated workflows, eliminating

deployment toil.

• Consolidated development infrastructure by 43% and parallelized ML workloads on GPU

instances, reducing build times by 80%.

• Developed an IaC platform with GitOps automation, reducing infrastructure fulfillment from

weeks to under 10 minutes (93% reduction), enabling self-service provisioning for ML research

and sales MVPs.

• Designed and developed PrimerCLI (Bash, Python, Go), a centralized developer toolkit

adopted by 100 engineers, reducing manual processes by 1,200 hours annually.

• Led the design and implementation of Kubernetes for the company's production migration to

Azure, achieving 46% completion and delivering $2.8M in cost savings.

A space technology company providing SAR imagery and satellite solutions for commercial and

government use.

• Reduced build times by 80% by creating a unified toolkit that eliminated 8,000 lines of

redundant code, containerized CI processes, and consolidated GitLab pipeline modules.

• Overhauled cloud infrastructure using IaC, improving code delivery reliability by 30% and

building a centralized tools cluster that enabled local-parity development and testing

environments.

• Built a redundant container registry for production systems, preventing satellite imagery

pipeline outages during peak collection windows.

Cloud governance automation solutions specializing in Security-as-Code to prevent data

breaches.

• Built the company's first CI/CD pipeline using Terraform and IaC (300 commits), integrating

AWS CloudFormation and Azure deployments and enabling 1.5+ production deliveries per day.

• Reduced production errors by 50% through expanded end-to-end testing, frontend and unit

test coverage, and automated monitoring and alerting.

• Built a speech model evaluation system adopted by 300 engineers and 80 PMs — comparing

quality data across usage history, forecasting performance, and shortening release cycles

through automated tooling.

• Developed automated Python tooling that cut 800 hours from data collection, using ML models

to detect user sentiment, map user journeys, and surface pain points.

• Sole designer of mouse-to-keyboard interaction for Google Assistant on web — filed for U.S.

patent.

• Managed GPU-focused cloud workloads and CI runners for speech model training and evaluation

pipelines.

• Led infrastructure migration enabling 100K+ Google employees to work remotely during

COVID-19 — maintaining communications, troubleshooting engineering environments, and adapting

internal tools for external access.

• Modernized ML build/release documentation for Assistant (5 years outdated, 2 tech stack

changes) — met with dozens of engineers to map processes for bleeding-edge ML release cycles.

• Volunteered for Google's AI Ethics advisory group (2019-2020), contributing to discussions

on responsible AI development, model interpretability, and evaluation standards.