principal engineer · 20 years in production · denver, co
➜ ~ cat bio.txt
I’m a hands-on engineer who keeps high-scale systems alive. Right now I architect AWS-native infrastructure handling hundreds of millions of daily requests for a real-time gaming platform — infrastructure as code, event-driven services, and data pipelines. After years leading as a CTO, I’m back where I do my best work: on the hardest problems.
The engineers who pull ahead won’t be the ones AI replaces — they’ll be the ones who wield it well. I treat models as production infrastructure: gated, non-blocking, and human-in-the-loop — never a bolt-on, never unsupervised. Used right, that leverage lets one engineer ship what used to take a team.
01
Leverage over headcount
AI-augmented workflows let a small, senior team — or a single engineer — ship what used to take a floor of engineers. I design the pipelines, prompts, and guardrails that turn that leverage into reliable throughput.
02
Judgment stays human
Models handle the toil — boilerplate, migrations, first-draft code and docs. Architecture, tradeoffs, and the call on what ‘good’ means stay where they belong: with the engineer.
03
LLMs as production systems
An AI feature is a distributed system like any other: async pipelines that never block the app, versioned prompts and models, observability, cost and latency budgets, and failure modes planned for up front.
04
Raising the team’s floor
The real multiplier isn’t my own output — it’s the tooling, standards, and review practices that make every engineer around me faster and safer with AI.
// in production — how I actually ship AI
Leverage, proven
A fleet of production and near-production Claude systems — a live trading optimizer, an agentic inbox brief, an AI video pipeline, a fitness coach — built and run largely solo. That breadth is only possible with AI leverage.
Gated, never unsupervised
Every model runs behind a gate. Claude annotates pull requests but never blocks a merge; a trading optimizer escalates suggest → paper → live only past a confidence bar, behind a circuit breaker; coaching stays descriptive, never prescriptive.
AI that never blocks
LLM calls are async, budgeted, and fallback-safe — a recording plays whether or not its AI summary is ready, and a two-tier Haiku/Sonnet split trades cost against depth per call.
> AI-first isn’t a tool you adopt. It’s how you architect, review, and ship — end to end.
01
Selected Work
// case studies
Consulting & roles// track record
Products & AI// shipped — most live
Open source & tooling// public
Hijack Poker
Real-time gaming platform at 300M requests/day
Architected and operate AWS-native infrastructure for an enterprise online poker platform — spanning online and brick-and-mortar operations, running 24/7. Built the real-time layer, the IaC, and the data engineering behind it, and lead an 18-person technology org.
CI/CDGitHub Actions→Automated Tests→Blue / Green Deploy→Backend + Unity clientsprovisioned via Pulumi
Kalshi-BotPersonal · AI-optimized trading system
A self-tuning fleet of prediction-market trading bots
A production fleet of algorithmic bots trading Kalshi’s short-window crypto prediction markets on momentum and trend signals — with Claude wired in to read live performance and propose strategy refinements. Containerized, deployed to AWS, running 24/7.
A daily agent that reads Email and Slack from the last 24h and synthesizes a ranked brief — urgent, committed, FYI — with Claude Sonnet. Each item opens a chat thread where the agent drafts tickets and replies.
Claude SonnetAgent ChatLaravelVue 3PWA PushAWS
// BRIEF PIPELINE — INGEST → SYNTHESIZE → ACT
SOURCES
Email · Slack
last 24h
→
SYNTHESIZE
Claude Sonnet
rank · cluster
→
BRIEF
3-Tier Digest
urgent · committed · fyi
⇢
ACT
Agent Chat
draft tickets / replies
DELIVERYQueued synthesis job→6am push→PWAan agent per item
jira-mcp
Open tooling · Model Context Protocol server
JIRA project intelligence, exposed as agent tools
An MCP server that exposes JIRA project health as tools any LLM client can call — surfacing blocked, stalled, and ‘bouncing’ tickets, at-risk epics, and transition bottlenecks for agentic project monitoring.
An open-source stack that puts whatever you’re building on a real HTTPS URL straight from your own machine — through a single outbound Cloudflare Tunnel, with Caddy routing each hostname to the right container. No server, no open ports, no deploy.
A fitness app with a conversational AI coach — Claude Sonnet with multi-turn memory and coaching personas — plus body-composition analysis from a photo (Claude Vision, through an S3 → SQS → Lambda pipeline). A real-time, on-device form coach is in progress.
Claude (Sonnet + Vision)LaravelVue 3CapacitorAWS LambdaSQSMediaConvert
// AI PIPELINE — CAPTURE → PROCESS → ANALYZE → COACH
CAPTURE
Photo / Video
mobile · Capacitor
→
PROCESS
S3 · SQS · Lambda
async · MediaConvert
→
ANALYZE
Claude Vision
body-fat % · quality
→
COACH
Claude Sonnet
memory · personas
⇢
BUILDING
Real-time form coach
MediaPipe · on-device
SHIPPEDPhoto body-comp→Conversational coach→HLS videoreal-time form coach in progress
A multi-tenant screen-recording platform — browser capture uploaded direct to S3 (the app server never touches video bytes), MediaConvert transcode to HLS, and a Claude + Transcribe pipeline for transcripts, summaries, chapters, and action items. In use internally and by external customers.
A cross-platform tracker for people running peptide, GLP-1, and hormone protocols — it remembers your regimen, schedules reminders, and handles the dosing and reconstitution math. It logs injections and bloodwork and imports Apple Health / Health Connect data, shipped as web plus native iOS and Android from one codebase.
LaravelVue 3CapacitorStripeApple Health / Health ConnectPostgreSQLRedis
// ARCHITECTURE — CLIENTS → API → ENGINE → DATA
CLIENTS
Web · iOS · Android
one Capacitor build
→
API
Laravel
api.pepme.ai
→
ENGINE
Protocol Engine
dosing math · schedule
→
DATA
Postgres · Redis
protocols · reminders
DELIVERYShared Vue + Capacitor→Push reminders→App Store + Playremembers · reminds · does the math
Maestro
Content platform · AI-assisted
Turning screen recordings into living documentation
A content-transformation platform that migrates, creates, and enhances documentation across SharePoint, Dozuki, and Confluence — including a desktop recorder that captures a workflow and turns it into a step-by-step SOP, with a versioned document-lifecycle engine underneath.
Architected the medallion data lake & warehouse strategy for a utility serving 3.7M+ consumers — Apache Iceberg tables, a two-phase CDC pipeline (row-hash updates, table-diff deletes), and a zero-downtime cutover from legacy Oracle.
Delivered security remediation across production apps and AWS environments — zero-trust microsegmentation with Illumio, Cognito/IAM identity hardening, encryption at rest and in transit, and an automated security-test suite.
IAM / VPCCognitoIllumio (Zero-Trust)EncryptionTest AutomationTerraform
// DEFENSE-IN-DEPTH — IDENTITY → NETWORK → DATA → AUDIT
IDENTITY
Cognito
OAuth2 · MFA
→
EDGE
API Gateway
security policies
→
NETWORK
Illumio
microsegmentation
→
DATA
Encryption
at rest / in transit
⇢
AUDIT
CloudWatch
logging · detection
SECURE CI/CDDependency scanning→Container hardening→Automated vuln scansleast-privilege IAM
Dun & Bradstreet
Solutions engineering for Sales & Marketing
In the Solutions Engineering group I built the internal applications that turned D&B’s commercial data into demonstrable value — a demo platform mapping every data package to real sales use cases, rolled out across the entire sales organization and wired into live engagements, and a self-serve sandbox where a customer uploads their own records and watches them get cleansed, standardized, and enriched with D&B firmographics in real time.
+10%
sales conversions
Org-wide
sales rollout
Data EnrichmentCleanse & StandardizeFirmographicsSales EnablementData Products
// ENRICHMENT PIPELINE — UPLOAD → CLEANSE → MATCH → ENRICH → VALUE
UPLOAD
Customer Data
own records
→
CLEANSE
Standardize
normalize · dedupe
→
MATCH
D&B Identity
entity resolution
→
ENRICH
Firmographics
data packages
→
VALUE
Proof
on their own data
DEMO PLATFORMEvery data package→Mapped to use cases→Tied to live sales+10% conversions
Apple
Developer Program identity & enrichment API
Every organization enrolling in the Apple Developer Program needs a DUNS number. As part of the D&B engagement I built the custom API embedded in Apple’s onboarding, registration, and login flows — it collects each developer’s details and enriches them against D&B in-line, resolving the DUNS number plus supporting firmographics. Shipped to production in 2017 and still in use today.
Dun & BradstreetCustom APIIdentity OnboardingDUNS ResolutionData EnrichmentIn prod since 2017
LIFECYCLEOnboarding→Registration→Loginproduction since 2017
Microsoft
Commercial data across the Common Data Service
Delivered the engineering behind the $500M Microsoft–D&B partnership that made D&B data supplementary across Microsoft’s Common Data Service. I built the secure connectivity between Microsoft and D&B’s internal APIs — authentication, rate limiting, and access controls — so CDS products could use D&B data as a live operational tool, plus the demonstration products used at trade shows and by the sales teams to drive the partnership forward.
Dun & Bradstreet$500M EngagementCDS IntegrationSecure API ConnectivityRate LimitingSales Enablement
Built an event-driven microservices platform for warehouse and supply-chain operations — decoupled services over a message backbone, with fault-tolerant integrations to third-party logistics systems.
RELIABILITYIdempotent handlers→Dead-letter queues→Automated retriesfault-tolerant by design
Whole Foods Market
SOX-compliant financial data platform
Delivered an encrypted data-transport and financial reporting platform with full audit traceability — moving sensitive financial data across systems under SOX controls, end to end.
// SECURE DATA FLOW — SOURCE → TRANSPORT → REPORTING → AUDIT
SOURCE
Financial Systems
transactions
→
TRANSPORT
Encrypted Transport
at rest / in transit
→
PROCESS
Reporting Pipeline
reconciliation
→
SERVE
Financial Reports
SOX controls
⇢
AUDIT
Audit Trail
full traceability
CONTROLSAccess controls→Immutable logs→Segregation of dutiesSOX-compliant
Timeless Medical Systems
The world’s first human-milk tracking system
As the sole developer, I built the world’s first human breast-milk tracking application — adopted by the Human Milk Banking Association of North America (HMBANA) across the majority of its facilities. I was also principal engineer on the hospital feeding solution that verifies, at the bedside, that every patient receives the correct feeding per the doctor’s order and the correct mother’s milk. A native PHP app on a custom framework, integrated with hospital EHRs like Cerner and Epic and deployed on-prem or in the cloud per site — built end to end for integrity and security: chain-of-custody, verification, and full audit traceability.
