---
title: "Jake Williams — Data & AI Platform Engineer"
canonical: https://jakeawilliams.com/
description: "Data & AI platform engineer — Kafka CDC streaming, a governed Snowflake lakehouse, and an enterprise Claude plugin marketplace used analyst to C-suite."
---

# The whole company asks questions of its data. I run the platform that answers.
I'm a data & AI platform engineer at a specialty insurer. I own the Kafka CDC streaming backbone, build core domains of the governed Snowflake lakehouse, and run the enterprise Claude plugin marketplace I spearheaded — 12 plugins, authored domain skills, and model evaluations across six business domains, used by everyone from analysts to the C-suite to answer business questions in plain English. Agentic analytics with governance, evals, and an audit trail — in production, not a pilot. Open to senior data-platform and AI/agent engineering roles — and AVP-level platform leadership in financial services.
info@jakeawilliams.com · copy ⧉ See the platform work → Résumé (print / PDF)

Williams — platform record, in production JW-01 Rev 2026-08 Sheet 01 01 Platform cost engineered out — Event Hubs → Kafka on Kubernetes $30K+/yr
02 Quarterly reserve review — governed natural-language analytics via marketplace plugins 3 days → <30 min
03 Claude plugin marketplace — ~200 monthly users (40% of company), 2K+ queries/mo 12 plugins
04 Certified — AWS Solutions Architect + Cloud Practitioner AWS SAA

The platform numbers are measured, not aspirational — each is expanded in a case study below.

02 · Selected work
## Platforms in production
Written the way platform work actually happens: constraints first, numbers where they're real, diagrams instead of proprietary detail.
Flagship · AI platform
### The Claude plugin marketplace
Created, built, and run the enterprise marketplace — 12 plugins and the authored domain skills behind them, spanning six business domains. Roughly 200 monthly active users — 40% of the company, five C-suite regulars — run 2K+ queries a month, at 30% lower token consumption than unassisted LLM use. I own the roadmap, the evaluations, the governance, and the support.
12 plugins · 6 domains
claude mcp ai agents llm evals
Case study →
AI & semantic analytics
### Semantic analytics in production
A production Claude + Snowflake Cortex layer where Claims, Policy & Underwriting, Finance, and Legal ask governed questions in plain English. The quarterly reserve review went from 3 days to under 30 minutes; QBR prep from 4 days to under an hour.
QBR prep: 4 days → <1 hr
snowflake cortex dbt python · sql
Case study →
Streaming platforms
### The CDC platform rescue
Inherited a half-built replication platform, shipped it, then re-architected it — Azure Event Hubs → Apache Kafka on Kubernetes, with Debezium CDC connectors (SQL Server, PostgreSQL, Oracle LogMiner), custom Java connectors where none existed, and type-2 period-fact modeling for historical questions.
$30K+/yr saved
kafka debezium kubernetes
Case study →
Observability
### Observability as code
Datadog and Prometheus dashboards shipped exclusively through GitHub Actions CI/CD, with forecast monitors that predict OOM and strain — the platform scales on signal instead of overprovisioning.
scale on signal
datadog prometheus gitops
Case study →

Open source — the work is public
### Waybill — bring receipts
A Claude Code plugin for token accounting on AI-assisted work: deterministic attribution of agent token spend to shipped work, evidence tiers, conservation checks, and verification packs a recipient can re-run offline. The same discipline as the day job — every number traceable to a receipt — with the code in the open.

claude code plugin agent metering MIT
github.com/Jakeintech/waybill ↗

03 · How I run it
## Platform leadership, in practice

### Own the number
Governance is the product. I run the BI tenant, so "governed" means the number is the same in the dashboard, the regulatory filing, and the chatbot — backed by SOC 2 SOPs and audit support.

### Raise the level
Code reviews, mentoring, and office hours leading the org's adoption of AI-assisted development. The platform gets better when the people around it do.

### Translate both ways
I serve every level of the business, analyst to executive, as the SME on feasibility, cost, and risk. That includes hands-on delivery — I built a key component of the enterprise pricing tool, a TypeScript microservice on Azure (GraphQL, MCP, PostgreSQL). Adoption decisions run on usage analytics, and model choices run on evaluations: evidence, not opinion, in both directions.

04 · Side projects
## Built to the same spec
Side work on iOS — Swift, SwiftUI, HealthKit, on-device AI, in the fitness and wellness space I actually live in. On-device, offline, no trackers — shipped only when it clears App Store review.

### QuotedAI
Quotes that know your moment — an on-device engine reads time of day, energy, and activity via HealthKit to surface the right words. No ads, no trackers. 2K+ downloads.
SwiftUI HealthKit on-device AI
App Store ↗

05 · About
## One standard, everywhere
I build and run enterprise data platforms in specialty insurance — the streaming backbone, core domains of the governed lakehouse, and the semantic layer that makes AI answers trustworthy. Off the clock it's open-source tooling, a side-project app, running, and yoga — different scales, same spec: build things that hold up under load.
More about me →

06 · Direct answers
### Who is Jake Williams?
A data & AI platform engineer at Vantage, a specialty insurer, where he owns the enterprise CDC/streaming platform (Apache Kafka on Kubernetes), leads engineering for a production Claude + Snowflake Cortex semantic-analytics system, and created the Claude plugin marketplace used across six business domains, analyst to C-suite. AWS certified; previously State Farm; author of the open-source Waybill plugin. Side projects include QuotedAI, an iOS app on the App Store.

### What is the Claude plugin marketplace?
An enterprise marketplace of 12 Claude plugins and authored domain skills spanning six business domains. Business leaders at every level — including the C-suite — use it to build QBRs, reserve reviews, financial reports, and canonical dashboards from governed data. Jake created it and runs its roadmap, governance, and support.

### What is semantic analytics?
Natural-language analytics built on an authored semantic layer — explicit definitions of metrics, domains, and joins — so an AI system answers from governed meaning rather than guessing at raw tables. Claude converses, Snowflake Cortex executes, and authored domain skills supply the semantics, keeping answers consistent with regulatory reporting.

### Why does governed AI matter in insurance?
Because an ungoverned answer is a liability with good grammar. Insurance runs on regulated definitions and access boundaries; AI analytics only works there if it inherits them — consistent metrics, respected permissions, an audit trail. That governance-first pattern is what separates production GenAI from stalled pilots.

### What does a data platform engineer do?
Builds and operates the infrastructure other data work stands on: ingestion and streaming (CDC, Kafka), the governed lakehouse (Snowflake, dbt, Dagster), orchestration, observability, and increasingly the semantic and AI layers. The product is the platform; its qualities are reliability, cost, governance, and trust.

### Is Jake available for new roles?
Yes — open to senior data-platform and AI/agent engineering roles (agentic systems, enterprise Claude platforms, MCP), and to AVP-level data-platform leadership in financial services. The fastest route is email (info@jakeawilliams.com) or LinkedIn (@jakeintech).

07 · The direct line
## Talk data & AI platforms.
Open to senior data-platform and AI/agent engineering roles — and AVP-level platform leadership in financial services. Also here to compare notes on governed AI analytics, Kafka cost engineering, and MCP in production. No forms, no calendar wall: a direct email gets a direct reply.
info@jakeawilliams.com · copy ⧉ LinkedIn ↗ GitHub ↗ All contact options →