Building practical, reliable software across the full stack.

JotGo is a SaaS platform and multi-browser extension for bug reporting and product feedback. It helps product, engineering, and QA teams capture screenshots, user activity, console logs, and network requests, then turn that context into work their teams can investigate and manage.

I led the platform rebuild as the primary technical decision-maker across the frontend, backend, browser extension, database, and MCP server. I coordinated three developers and two QA engineers while setting implementation priorities and managing releases across multiple repositories.

• Built a Pixi.js and WebGL canvas renderer while retaining the inherited ReactFlow implementation as a fallback. The old canvas began lagging past around 100 images, while the new renderer stayed usable to around 1,000 in generated-data testing, roughly 10x the previous capacity. Production usage sat in the hundreds.
• Implemented Firestore-based real-time synchronization for the canvas, allowing multiple users to see canvas updates as they occurred without refreshing the page.
• Built session replay and browser-extension diagnostics end to end across the extension, frontend, and backend. The feature combined user-action capture and playback with console-log and network-request collection, giving customer teams more context for investigating reported issues.
• Built the GraphQL-based Linear integration, then developed webhook-driven two-way synchronization between JotGo and Linear. Also fixed webhook handling and shared issue fields and actions across the inherited Jira integration.
• Built and shipped an MCP server that allows users to access and work with platform feedback through supported AI tools using Auth0-based OAuth or personal access tokens.

Enterprise AdTech platform for campaign, line item, ad group, targeting, optimization, and audience management. I was the only Digital Avenues developer working directly with Cadent's US-based development team and followed its Eastern Time schedule.

My work was concentrated in ad-group optimization and audience workflows, where interdependent settings, asynchronous data, validation, and shared state had to remain consistent across multi-step creation and editing flows.

• Built the core ad-group optimization experience in React and TypeScript, using controlled form state, React context, and REST APIs to keep bidding, optimizer, predictive-model, and validation behavior synchronized during creation and editing.
• Built administrative workflows for managing predictive models with React Hook Form, including cross-field validation, conditional fields, access scoping, and bulk updates released behind feature flags.
• Built healthcare-audience targeting within a multi-step ad-group setup workflow, preserving selections across creation and editing so users could navigate the workflow and revise targeting without losing their work.
• Built configurable audience controls with predefined and custom score ranges, giving users direct control over the balance between targeting quality and potential reach for each campaign.

Standalone healthcare audience-building product for estimating audience size and reach from clinical, insurance, provider, demographic, location, cost, and date-of-service criteria. It also provided media insights across publishers, channels, and devices.

I took over final delivery of the inherited product when the US team no longer had capacity to complete it before the planned release.

• Coordinated QA across multiple environment branches, delegated fixes, resolved blockers directly, and promoted three releases to production within roughly one month.
• Stabilized core audience-building and results workflows by resolving frontend, Razor-view, and API issues affecting audience saves, reach calculations, duplicate submissions, date-of-service filters, chart rendering, and generated results.
• Validated returned data and product behavior with the US Product Owner and data warehouse team, resolving data and UI discrepancies before production.

Long-running AdTech campaign management platform covering campaigns, line items, strategies, targeting, audiences, reporting, and forecasting. My work was frontend-heavy across JavaScript and Razor, with backend responsibility in C#, ADO.NET data-access and business-logic layers, WCF services, and SQL Server.

• Built and enhanced targeting workflows across geographic, point-of-interest, device, network, video and CTV, audience, and frequency-cap criteria, integrating MVC views with API and WCF-backed flows.
• Implemented multi-currency support across the MVC and Angular applications, carrying currency context, values, and formatting through campaign, forecasting, marketplace, audience, and reporting workflows.
• Improved zip-code map performance for large selections by moving coordinate lookup from the browser's main thread into a web worker before plotting markers, reducing interface blocking during map-based targeting.
• Implemented C# changes across ADO.NET data-access and business-logic layers, wrote stored procedures when needed, and traced requests through WCF services and SQL Server to resolve cross-layer data and business-rule defects.
• Extended the existing reporting console with SFTP delivery for generated CSV, Excel, and ZIP files, allowing reports to be sent directly to client-managed infrastructure instead of relying only on email.
• Diagnosed and resolved production issues across campaign and targeting workflows, while mentoring junior developers through pair debugging and code reviews.