Nick Anthony
@nickanthony
I’m a staff-level AI/ML engineer building full-stack data platforms with GenAI that cut latency and boost reliability.
United StatesWhat I'm looking for
I’m a staff-level AI/ML Full Stack & Data Engineer with 10+ years of experience building customer-facing, data-intensive products powered by Python and TypeScript. I bring deep expertise in GenAI (LLMs, RAG, Agentic AI, Multi-Agent Systems) and scalable data platforms, and I’m known for leading zero to one and one to N systems. I enjoy end-to-end ownership across data, backend, and frontend layers in fast-paced startup environments.
At Oscar Health, I led development of multiple AI products and data platforms serving over 1M users, owning architecture, delivery, and cross-functional execution. I built a GenAI + Agentic AI member support assistant for 500K+ monthly users, reducing support tickets by 35%, and I delivered RAG pipelines that improved retrieval accuracy by 30% while keeping embeddings and knowledge bases fresh.
Previously at Brex, I scaled early-stage fintech capabilities into high-growth systems, including a real-time fraud detection platform that reached 100K+ transactions/minute and reduced fraud losses by 20%. I’ve continued to combine strong data engineering fundamentals with practical full-stack delivery—whether through Kafka-based streaming, ELT/data modeling, or building customer-facing dashboards and APIs—while mentoring teams and establishing best practices for reliability and observability.
Experience
Work history, roles, and key accomplishments
Led development of multiple customer-facing AI products and data platforms serving 1M+ users, improving personalization quality and real-time data availability. Delivered a GenAI member support assistant for 500K+ monthly users and reduced support ticket volume by 35% while building RAG pipelines and scalable inference services.
Scaled fintech systems from early-stage to high-growth by building customer-facing AI features and real-time data pipelines. Built a real-time fraud detection platform scaling to 100K+ transactions per minute and reduced fraud losses by 20% while improving precision and reducing false positives by 15%.
Built customer-facing financial analytics platforms using Python, SQL, and Java backend services, turning complex datasets into structured insights. Developed ETL pipelines and APIs for real-time and batch metrics, and improved planning and risk analysis accuracy by 15% through predictive and rule-based systems.
Developed backend services and data processing pipelines using Python and SQL to support enterprise reporting and analytics dashboards. Optimized database queries and backend workflows, reducing execution time by 30% and improving overall application responsiveness.
Developed backend modules and data-driven features using Java and SQL for customer-facing enterprise applications. Wrote optimized SQL queries and supported production stability through debugging, testing, and maintenance of backend systems.
Education
Degrees, certifications, and relevant coursework
University of California, Los Angeles
Bachelor of Science, Computer Science
2008 - 2012
Earned a Bachelor of Science in Computer Science at UCLA from 2008 to 2012.
Tech stack
Software and tools used professionally
Kubernetes
Pandas
PySpark
dbt
PostgreSQL
MongoDB
Node.js
Django
Spring Boot
Next.js
Tailwind CSS
Redis
Terraform
React
JavaScript
Python
HTML5
Java
CSS 3
TensorFlow
PyTorch
scikit-learn
Kafka
FastAPI
SQLAlchemy
GraphQL
TypeScript
Airflow
s3-lambda
SQL
LangChain
LlamaIndex
Pinecone
Delta Lake
Cursor
Agentic
Faiss
LangGraph
Keep
Brex
Stack AI
Task
Jan
Availability
Location
United StatesAuthorized to work in
Salary expectations
Social media
Job categories
Skills
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