Nay Systems Production-ready Data and AI

Founder-led engineering leadership

Engineering leadership for systems where getting it wrong isn't an option

When ownership is fragmented, delivery is uneven, and the business cannot afford to stop, Nay Systems brings the platform judgment, operating discipline, and team leadership to get it right.

20+ years 39-person global org $11.4M org scope Analytics, fraud, security, AI

What I do

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 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.

Where I'm usually brought in

The pattern is usually familiar. Delivery pressure is high. Platform maturity is uneven. Governance is weak or contested. Everyone wants speed, but no one can afford another visible failure.

  • Legacy and modern platform approaches are colliding
  • AI urgency is outrunning platform readiness
  • Teams are shipping, but trust in the data is inconsistent
  • Governance exists in principle, not in delivery
  • Ownership is fragmented across engineering, data, and business teams
  • The business needs quick wins without accumulating more debt

How I work

I do not start with tool worship or transformation slogans. I start with what has to hold up in production, what the business cannot afford to get wrong, and what operating structure the team needs to deliver under pressure.

01

Stabilize what matters

Identify the systems, metrics, workflows, and decisions that carry the highest consequence. Reduce noise. Create immediate control.

02

Create the operating model

Clarify ownership, standards, decision paths, and delivery mechanisms so teams can move with less friction and fewer surprises.

03

Modernize for scale

Upgrade the platform, workflow, and governance model in a way that improves speed, trust, and long-term maintainability.

Selected work

A few examples of the kinds of systems and environments I've led.

AI / Data Platforms

AI-powered analytics onboarding

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.

Security / Risk

Fraud and identity resolution platform

10% 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.

Data Infrastructure

Petabyte-scale data platform

Full-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.

About Jeremy Nay

I'm an engineering leader with more than 20 years of experience building data platforms, security systems, and the organizations that own them. I operate where strategy meets execution - translating ambiguous mandates into clear ownership, durable systems, and teams that deliver reliably at scale.

I'm most effective where decisions are one-way, the cost of mistakes is real, and someone must be held accountable for outcomes, not just effort. I treat AI as a system component, not a feature: production guardrails, deterministic validation, and human accountability for correctness and meaning are non-negotiable. Nay Systems is the vehicle for that work.

Based in Seattle. When not building systems, I race yachts on Puget Sound and serve as Secretary of the Puget Sound Bonsai Association. Clear ownership, long-term stewardship, and showing up when it matters.

Jeremy Nay

What I believe

In the enterprise there is no room for heroics. Only consistency, accountability, and trust.
AI is a governance problem, not a feature. Humans must remain accountable for correctness and meaning.
Clearing technical debt is mandatory, and it can happen while delivering real business value.

Need to modernize without stopping delivery?

Let's talk if your platform, data, or AI systems need stronger foundations, clearer ownership, and a path to scale that holds up in production.

Start a conversation jeremy@nay.systems