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Gordon Macmillan

@gordonmacmillan

I build production generative AI and risk platforms that improve fraud, KYC, and underwriting decisions.

United States
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What I'm looking for

I'm looking to build secure, explainable production AI systems for complex risk, fraud, document intelligence, and financial-crime workflows, with strong engineering standards, human review, cloud-scale delivery, and opportunities to lead technical design and mentor teams.

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

Shift Technology logoST

Senior AI/ML Engineer

Sep 2024 - Jul 2026 (1 year 10 months)

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.

Kira Systems logoKS

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%.

Education

Degrees, certifications, and relevant coursework

Harvard University logoHU

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 logoUD

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.

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