01 - What I Do
Capabilities
Data Platform Leadership
Platform readiness, governance, migration strategy, and boundary judgment at enterprise scale. When shared infrastructure falls short, I extend it, block premature adoption, or build a bridge.
AI-Enabled Workflow Design
Production RAG pipelines, LLM integration, and automated schema validation with explicit guardrails. Humans accountable for correctness and meaning. AI handles the mechanical precision work.
Security and Risk Systems
Fraud detection, identity resolution, IAM, SOX/GRC compliance, and CISO-level reporting infrastructure. Systems where failure modes escalate to the C-suite and the cost of mistakes is real.
Operating Model and Org Design
Global team unification, shared operating models, decision latency reduction, and leadership bench development. I build organizations that hold up under pressure, growth, and change.
02 - Selected Work
Results
Collapsed analytics onboarding from days to hours. Freed more than $2M in annual engineering capacity for higher-leverage work.
Identified analytics onboarding as a systemic engineering failure, not a staffing problem. Designed a RAG-grounded pipeline: hybrid Elasticsearch retrieval, LLM-generated SQL with automated schema validation, governed YAML output, and automated GitHub PR creation. The LLM operated only on approved, indexed schemas. Human review required before merge.
AI / Data Platforms10% year-over-year fraud loss reduction. Multi-brand scale. Sev1 incident contained under live booking-path pressure.
Re-architected two monolithic fraud services into a distributed identity resolution platform with stateful behavioral graphing, ML scoring, explicit rules execution, and full audit persistence. Operated at booking-path speed across a multi-brand portfolio. Judgment forged under real production pressure.
Security / RiskFull-stack ownership from cluster to application layer. 400% production capacity expansion. Live infrastructure migration at petabyte scale.
Built and operated a Lambda Architecture for a social intelligence product before managed cloud services existed for this class of workload. Kafka ingestion, HBase storage, MapReduce enrichment, Elasticsearch query serving. Owned everything from bare metal to the pixel on screen.
Data Infrastructure03 - About
Background
Jeremy Nay is an engineering leader with rich experience building data platforms, security systems, and the organizations that own them. He operates across strategy and execution, translating ambiguous mandates into clear ownership, durable systems, and teams that deliver reliably at scale.
His focus is platform boundary judgment - knowing when shared infrastructure is safe to use, when it needs extension, and when to build a bridge. He treats AI as a system component, not a feature: production guardrails, deterministic validation, and human accountability for correctness and meaning are non-negotiable. His teams consistently deliver above expectations without sacrificing operational discipline.
Based in Seattle. When not building systems, he races yachts on Puget Sound and serves as Secretary of the Puget Sound Bonsai Association. Clear ownership, long-term stewardship, and showing up when it matters.