
Gordon Macmillan
@gordonmacmillan
I build production generative AI and risk platforms that improve fraud, KYC, and underwriting decisions.
What I'm looking for
I've delivered production AI systems at Shift Technology, FTI Consulting, Stripe, Kira Systems, and Pristine. My work turns complex documents, transactions, and policies into evidence-backed decisions for fraud, underwriting, financial crime, and contract analysis.
At Shift Technology, I built agentic document intelligence and hybrid RAG workflows for claims fraud and underwriting risk using Microsoft AI Foundry, Microsoft Fabric, Azure AI Search, Azure OpenAI, Temporal, and graph services. At FTI Consulting, I delivered a financial crime intelligence platform that reduced KYC investigation turnaround by approximately 60% and improved analyst research efficiency by approximately 55%.
At Stripe, I improved fraud capture by approximately 12% while reducing false-positive payment blocks by approximately 10%. I build secure, explainable AI across Azure, GCP, and AWS, with practical focus on MLOps, governance, human review, and reliable production delivery.
Experience
Work history, roles, and key accomplishments
Delivered production AI capabilities for fraud and underwriting risk detection using Microsoft AI Foundry and Fabric, building data pipelines, agent workflows, and hybrid RAG systems. Mentored engineers and contributed to Agile/Scrum delivery.
Delivered a cloud-based financial crime intelligence platform supporting KYC, entity resolution, and transaction monitoring. Built GCP data pipelines and AI agents, improving KYC investigation turnaround by 60% and analyst efficiency by 55%.
Enhanced Stripe Radar 2.0, a real-time payment risk platform, by engineering ML features and fraud detection models. Improved fraud capture by 12% and reduced false-positive blocks by 10% while maintaining low-latency inference.
Machine Learning Engineer
Kira Systems
Sep 2016 - May 2018 (1 year 8 months)
Developed ML capabilities for the Kira Contract Analysis Platform, including document processing pipelines and clause classification models. Improved F1-score from 0.82 to 0.90 and reduced annotation effort by 35%.
Software Engineer
Pristine, Inc.
Nov 2014 - Jul 2016 (1 year 8 months)
Built Pristine EyeSight, a multi-tenant SaaS platform for smart-glasses remote assistance. Developed backend services and web applications, improving database performance by 30%.
Education
Degrees, certifications, and relevant coursework
Harvard University
Master of Science, Computer Science
2012 - 2014
Master's Degree in Computer Science from Harvard University, completed from 2012 to 2014.
University of Texas at Dallas
Bachelor of Science, Computer Science
2008 - 2012
Bachelor's Degree in Computer Science from the University of Texas at Dallas, completed from 2008 to 2012.
Tech stack
Software and tools used professionally
OpenAPI
Apache Spark
GitHub
Kubernetes
Jenkins
PySpark
MySQL
PostgreSQL
MongoDB
.NET
Databricks
Neo4j
Redis
Terraform
Jira
AngularJS
JavaScript
Java
ASP.NET
TensorFlow
PyTorch
scikit-learn
Azure Service Bus
FastAPI
OpenTelemetry
NLP Cloud
Gemini
Gordon
WebRTC
GuardRails
SQL
XGBoost
Hugging Face
Temporal
Qdrant
LangChain
Weaviate
ChromaDB
Foundry
Pinecone
Ragas
pgvector
Agentic
Faiss
LangGraph
LangSmith
Microsoft Fabric
PEFT
Durable
Availability
Location
Authorized to work in
Job categories
Skills
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