Solutions Engineer · Observability & Customer Engineering
I find it. I explain it. I take it upstream.
Nine-plus years turning production failures in enterprise Azure systems into dashboards, runbooks, and training to prevent the next one. Now doing that with customers, upstream.
I think of documentation as a radical act of empathy from my current self to the future self who will not have a time machine.
What I Do
Technical Discovery & Escalation Ownership
I trace a customer's problem until I understand the system well enough to explain it back to them. At Cogstate that means working across a platform of .NET microservices on Azure, with React front ends and SQL Server, Cosmos DB, and Databricks behind them, usually by way of a great deal of KQL, and often turning up race conditions and architectural bottlenecks along the way. Once the cause is clear, I size the production risk, get the right teams moving on remediation, and document the failure pattern, since the same thing has a way of breaking twice.
Customer Enablement
Runbooks, KB articles, tutorials, and training sessions have run through most of my career, going back to my time as a software trainer at the USPTO. At Accenture Federal Services, I trained people on the HoloLens, ran troubleshooting training for client support teams, and built a knowledge base that cut repeat requests 15% in three months. At Trove, my onboarding documentation took five hours off a new engineer's ramp-up, and the regular training I ran for the support team cut escalations 30%, alongside tutorials and release-day support. At Cogstate, I write the runbooks for failures we've seen before.
Voice of the Customer
I read the support queue in aggregate, looking for the patterns that only show up across many tickets, then turn them into product conversations. At Trove, a feedback loop I built between support and product produced three shipped features and a 25% drop in repeat requests within six months.
Solution Design & Tooling
When a manual step keeps coming back, I build the script or app that removes it; my tolerance for doing the same task by hand runs out at about two repetitions. Over the years, that instinct has produced maintenance automation that returned 30 hours a month to my team at AIS, a streamlined data collection process at Guidehouse that saved more than 200 hours a year, and the hands-free warehouse photo pipeline described below.
Building Software
Underneath the customer-facing work is real engineering. At Trove I designed and shipped internal applications in React, Python, and SQL, shaving an average of five seconds off their load times, and I was the sole owner of the warehouse photography workstream detailed in the case study below. Before that, as a software engineer at AIS, I worked on a Department of Defense contract in .NET architecture, paying down tech debt and contributing meaningfully to the broader engineering organization.
Stack
My current environment at Cogstate is a .NET microservices architecture on Azure, with React front ends and data layers in SQL Server, Cosmos DB, and Databricks.
Languages
Front End
APIs and Services
Data, Cloud, Observability
Workflow
Trajectory
Application Support Engineer · Cogstate
I own technical investigations end to end across the .NET microservices and React front ends behind Cogstate's clinical data pipelines, on Azure, where accuracy has scientific consequences. Tracing data from creation to the report where it surfaced wrong, then turning findings into remediation plans, runbooks, and summaries leadership can act on.
Product Support Engineer · Trove Recommerce
I was the technical escalation point on a high-volume resale platform, handling tier 2 and 3 escalations for partners and running the feedback loop from their tickets back to product. I also shipped custom applications in React, Python, and SQL, created tutorials and provided day-of support for product releases as the primary subject matter expert for triage, and served as sole owner of the warehouse photography workstream, working across internal teams and external clients from across the country.
Next-Gen Research Engineer · Accenture Federal Services
I owned SharePoint deployments start to finish: requirements, deployment, testing, and sign-off. I also worked with Matterport 3D capture, Microsoft HoloLens, and Skydio drones, trained people on the HoloLens, and researched emerging technology for leadership, including early evaluation of ChatGPT. The work was recognized with a Department of State award for delivery.
Junior Software Engineer · Applied Information Sciences
On a Department of Defense contract, I worked with senior engineers on design, development, and testing across .NET, Python, and JavaScript applications, and paid down tech debt along the way. Resolved 100+ bugs and helped deliver five major projects ahead of schedule. Automating routine maintenance gave the team back 30 hours a month.
Technology Consultant · Guidehouse & CGI Group
I managed the product backlog on a $6 billion federal project, built my first RESTful API integrations, and supported 11,000+ users. Streamlining the data collection process saved 200+ hours a year.
Case Study
A Shutter-to-Retouch Photo Pipeline for Warehouse Operations
SE lens: The customer was a warehouse team and an external retouching partner. The problem was a workflow that left less-technical users stuck in multi-week ticket loops. I scoped the requirements with both sides, rebuilt the capture app so a single keystroke handled photo, metadata, and notes, documented it, and instrumented it with telemetry.
The Situation
At Trove I was the sole owner of the workstream where photography met technology: a warehouse across the country from me, serving customers in stores nationwide, with work that spanned internal teams and external clients. Every item that came through needed photos, metadata, and notes before it could be listed for resale. Team members were often juggling arcane bugs between CaptureOne, the warehouse cameras, item records, Google Drive, and the retouching service, and less technical team members were often left with tickets open for weeks with zero recourse.
The Approach
I rebuilt the capture app in Python and Tkinter, using AppleScript to connect CaptureOne directly to the warehouse cameras, so that a single keystroke saved the photo, its metadata, and the item notes together. Every shot went straight to Google Drive, where a cron job carried files to the retouching service and delivered the finished images back.
The Result
The new app improved partner onboarding, let photographers keep their hands on the camera, and put an end to metadata going missing between systems. I also wrote its documentation and instrumented it with telemetry that tracked myriad things, because I wanted all the information I could get about how it was running.
Projects & Ideas
Data & observability
Music Library Pipeline
BuildingA pipeline that takes a library of tracks, parses the titles, matches them against MusicBrainz candidates, and models the result with dbt on a local DuckDB warehouse. It keeps a running log of what broke along the way, and a session-state file so work resumes cleanly.
NYC Taxi Pipeline
ShippedAn ELT pipeline over New York City's public taxi trip data, in which DuckDB reads Parquet files directly from the TLC's servers, dbt models them into daily and hourly marts, and schema tests guard data quality on every build. The whole thing lives in a GitHub Codespace, and the documentation site is generated from the pipeline itself. Source · Docs site
R09 Ring Dashboard
WorkingReads a Colmi R09 smart ring over Bluetooth LE and stores heart rate, sleep, SpO2, HRV, stress, and steps in SQLite, then serves a local dashboard. The hard part was reverse-engineering the ring’s protocol and getting macOS to share the Bluetooth link.
Products & tools
Zubaan
BuildingA single-user language tutor for French, Levantine Arabic, Swahili, and Mandarin. One server-side OpenAI call per learner turn, FSRS spaced repetition for review, and all learner state kept in the browser.
Ladder
BuildingA rehabilitation gym for an engineer returning to the craft, built around the rule that completion is gated by evidence, never by a click. Lessons, rubrics, and a deterministic scorer are all validated against a typed schema.
Cognitive Resistance Gym
BuildingShort structured exercises followed by Socratic AI coaching, meant to train the habit of staying the author of your own reasoning. The first vertical slice, a Contradiction Lab station, runs end to end against a mocked coach.
Earworm
BuildingA music meditation app, built on the premise that whatever song is stuck in my head usually means something. Each entry pairs the song with whatever it dragged up, and each month's reflections resolve into a word cloud of what I kept returning to. It's built in React, TypeScript, and Vite, and saves to the browser for now. Source
Off the Clock
Photography
I'm a photographer on the side, with a habit of noticing how an image gets from the shutter to wherever it ends up.
Music
I curate music. Earworm is where I keep whatever song has taken up residence in my head, and the Music Library Pipeline is where I tame the rest of the collection.
Art
I curate art, and chase anything that gives me frisson, whether it arrives through a gallery wall, a film, or a song.
Now
At Cogstate
As an application support engineer at Cogstate, I work as senior support engineer, systems analyst, and production steward at once, for the .NET microservices on Azure behind the company's clinical trial data. I trace data from the moment a trial participant is created to the report where something surfaced wrong, then translate what I find into remediation plans, Jira tickets, and summaries leadership can act on.
The work puts me in regular contact with product, science, DevOps, engineering, client support, and outside partners, and I serve as the bridge between technical investigation and business-facing communication.
Building
Earworm; this site and its blog; and a small Claude Code clone through CodeCrafters, which is working its way up to the tool-calling loop. I build with Claude Code, and writing my own version of it is how I'm learning what it's actually doing under the hood.
Data Engineering in an AI World
The pipelines, data quality, and observability that AI systems quietly depend on. My day job already involves data integrity work across Databricks, Cosmos DB, and SQL Server, and the NYC Taxi pipeline is where I practice the modern side of the stack with dbt and DuckDB.
AI-Assisted Engineering
How assistants like Claude Code change the scope of what a single engineer can own, and how much of a support queue an assistant can handle well before it needs someone who genuinely knows the system.
Cleared Roles
I hold an active Secret clearance and am open to roles that require one. Get in touch and I'll send the right résumé.
Get in Touch
I'm looking for Solutions Engineering roles in observability, data, and developer tools. If that sounds like your team, I'd love to talk.