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.
The platform numbers are measured, not aspirational — each is expanded in a case study below.
Platforms in production
Written the way platform work actually happens: constraints first, numbers where they're real, diagrams instead of proprietary detail.
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
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
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
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
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.
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.
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.
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).
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.