Brian McDaniel

- Built the Beech Valley platform from zero to production, scaling to 400k+ candidate applications and thousands of vetted consultants, leading development across the React frontend, Node/GraphQL/PostgreSQL APIs, and AWS infrastructure. - Led the design and implementation of the applicant vetting workflow, cutting average vetting time from 25 to 12 days by replacing a multi-spreadsheet process with an in-product experience. - Designed and built core consultant/project matching workflow into the product, reducing the time to present candidates to clients from days to hours and turning speed of delivery into a key competitive advantage. - Implemented semantic search using OpenAI embeddings + pgvector, enabling direct consultant matching from text-based job descriptions instead of manual filtering. - Architected and led migration from Heroku to a multi-account AWS architecture (ALB, ECS, RDS, Terraform), improving performance, security boundaries, and cost efficiency. - Developed automated commission calculation system supporting multiple commission structures, unblocking accounting system migration that saved $60K annually. - Established full-stack TypeScript Nx monorepo with end-to-end type safety, generating types from GraphQL schema to catch breaking changes at compile time. - Ensured data consistency in core workflows via state machine architecture, implementing locking and enforcing preconditions to prevent race conditions. - Hired and led cross-functional team of 5, establishing culture of automated testing, code reviews, CI/CD, observability, and RFC-based architecture planning.

- Provided full-stack engineering for clients in EdTech, nonprofit, fitness, and retail sectors. - Delivered 8 web applications, both as a solo developer and as a tech lead, primarily using TypeScript, Node.js, Angular, React, Postgres, and Heroku. - Led frontend development for an Angular.js SPA used by 100,000+ teachers, evolving it from prototype to stable production system. Continually modernized the tech stack over six years by adopting TypeScript, introducing Webpack, and migrating from Angular 1.x to Angular 2+. - Built the frontend for a real-time structured document editor using WebSockets, enabling Google Docs-like multi-user editing. - Presented Angular best practices talk to 50+ developers at the RVA.js meetup and to a client company.

- Contributed to Rackspace's cloud management platform serving thousands of customers, implementing features across the customer-facing control panel. - Acted as tech lead on the Billing Page implementation, enabling customers to manage payment methods, view current charges, and download past invoices. - Co-presented a tech talk on CI/CD best practices to the entire Blacksburg office, which was recorded and shared across the entire engineering org. - Prototyped integrating Knockout.js into our tech stack and presented my findings at a team lunch-n-learn.

- For my master's thesis, I created a server-centric web framework called CloudBrowser using Node.js, JavaScript, and C++. - Designed and implemented a custom synchronization protocol to mirror server-side application instances to 1 or more frontend clients. - Created Contextify, a C++ module for Node.js that fixed several fundamental issues with Node's built-in VM module. Contextify was later merged into Node.js itself, replacing the existing VM module implementation. - Contributed to several open source projects, including JSDOM and Zombie.js. - Practiced TDD and created a comprehensive test suite for the framework.

- Studied the structure of software (both static relationships between components and runtime behavior) through a complex networks lens. - Used Valgrind (with the Callgrind plugin) to collect function call data on running programs. - Wrote a custom LLVM plugin in C++ to map out static relationships between functions. - Wrote a Ruby program (with a GTK+ GUI) to parse the resulting output files and look for statistical relationships between components. - Incorporated an open-source Matlab library for doing power law analysis and parallelized it for use on a 64-processor cluster.

- Analyzed run-time performance of embedded devices by hooking into the Windows CE kernel and monitoring the time spent in each thread. - Wrote kernel code to send context switch information to a logic analyzer using a binary protocol I designed, allowing me to identify long-running threads. - Wrote a C++ program to analyze the large output files from the logic analyzer and compute run time statistics. - Used the results from my analysis to identify 2 slow device drivers, then refactored them to improve performance by 10x in one and 3x in the other.