Your work impact reads senior-level, but a nearly-empty-star GitHub underplays that you’ve already shipped tax-critical and memory-critical systems.

From sales tax flows to cognitive memories, you repeatedly design pipelines that turn noisy events into structured, queryable threads.

You don’t just bolt on LLMs—you wrap them in retrieval, decay, BFS graphs, and priority weights that respect latency and accuracy targets.

Your most advanced agentic and recall engines live in job bullets, not in public repos or technical write-ups yet.

Interview and assessment repos aren’t bare answers; they’re packaged with frontends, narratives, and end-to-end flows—your instinct is to turn even evaluations into believable products.

From candidate recommendation and new-grad listings to advisor meeting copilots, your projects cluster around decision-heavy human workflows—you're drawn to augmenting judgment, not just automating tasks.

Forking active, fast-moving projects (job boards, agent frameworks) and building adjacent experiments reveals a bias toward immersing yourself in live ecosystems instead of isolated tutorials.

CVS UX redesigns, pixel-perfect GMGN clones, and React+FastAPI copilots all start from user flow and presentation—your engineering choices seem downstream of an unusually strong product/UX intuition.