Brian Ho
@brianho
I build scalable backends and AI-powered document understanding for real products.
What I'm looking for
I’m a Software Engineer with 8+ years of experience building scalable web applications, backend platforms, APIs, and data-driven product features across real estate, fraud prevention, marketplace, fintech, and consumer technology. I started in full-stack product engineering and distributed backend services, then expanded into ML-powered platforms and production AI applications.
At First American, I built AI document-understanding features for title and real estate workflows in AgentNet using Python, FastAPI, GraphQL, AWS, and Azure OpenAI. I implemented OCR and extraction pipelines with Textract, S3, SQS, ECS, and CloudWatch; integrated GPT-4o for structured extraction with JSON schema validation, confidence scoring, and fallback handling; and exposed provenance, confidence, reviewer edits, workflow status, and audit history via GraphQL. I also used OpenSearch for document search and context retrieval, added async processing for long-running jobs, and monitored AI workflows with CloudWatch and structured logs.
Previously at Sift, I engineered real-time fraud decisioning services and event-ingestion APIs using Java, Go, gRPC, REST, Kafka, PostgreSQL, Redis, and Kubernetes—enabling low-latency approval/block/step-up flows and analyst review workflows. Earlier, at Jobox.ai, I built marketplace backend features including an Elasticsearch-based search system and payment/integrations (Stripe, Twilio 2FA). I bring strong production instincts—observability, reliability, and system design—alongside hands-on AI integration (RAG, document understanding, evaluation, and prompt/version tracking).
Experience
Work history, roles, and key accomplishments
Built AI document-understanding features for title and real estate workflows, integrating OCR/extraction pipelines and Azure OpenAI GPT-4o for structured field extraction with confidence scoring. Developed GraphQL APIs and OpenSearch-backed search/retrieval, and monitored AI workflows with CloudWatch and structured logs.
Developed real-time fraud decisioning services, event-ingestion APIs, and backend workflows for marketplace and e-commerce risk use cases using streamed customer events and low-latency caching. Built fraud-review APIs for analysts and added production monitoring for ingestion lag, scoring latency, and decision errors.
Software Engineer
Jobox.ai
Apr 2019 - Jul 2020 (1 year 3 months)
Built marketplace backend features including an Elasticsearch-based search system with filtering, ranking, pagination, and permission-aware visibility rules. Implemented payments and wallet workflows with Stripe and security features like Twilio-based 2FA with Redis-backed sessions.
Built a microservice for Alexa News to parallelize and diagnose media-processing jobs, improving reliability with retry and job-level error handling. Added logging and operational visibility to enable faster reruns of failed processing workflows.
Software Engineer Intern
Asaii
Jun 2017 - Aug 2017 (2 months)
Developed analytics export and user tracking workflows for a music analytics platform to support personalized article experiences. Enabled tracking of user-specific interactions for engagement analysis and reporting.
Education
Degrees, certifications, and relevant coursework
University of California, Berkeley
Bachelor of Arts, Computer Science
2014 - 2018
Activities and societies: Volunteered with the Hepatitis B Project (Jan 2015–May 2015), helping create and maintain the project website and support patient education, screening, and vaccinations at a clinic in Oakland.
Earned a BA in Computer Science at UC Berkeley, with a specialization that combined Computer Science and Cognitive Science coursework.
Availability
Location
Authorized to work in
Job categories
Skills
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