Victoria Essien

About Me

I'm a full-stack engineer shipping production software across Next.js/React (TypeScript) on the frontend and FastAPI/Python on the backend. I work end-to-end: API design, schema work, UI, performance, and the production bugs nobody wants to debug.

At Baza Analytics, I'm building an AI-powered analytics platform: multi-tenant auth, secure credential storage on GCP Secret Manager, role-based access control, streaming AI query pipelines, and five different ways for users to connect their data and query it through our AI agent. When something breaks in production, whether it's auth race conditions, RLS failures, LLM agent loops, or streaming errors, I'm usually the one debugging it.

Before Baza, I led delivery at Tison (sprint planning, code reviews, client-facing) and shipped UI at DirectEd Development. My background started in design, which is why my frontend looks designed instead of assembled, and why I'm comfortable making product calls, not just executing tickets.

Open to engineering roles, product engineering roles, and select consulting work.

What I've Shipped

Case Study · Current Role

Baza Analytics

AI-powered analytics platform for non-technical teams. I work across the stack: shipped multi-tenant workspaces with RLS-backed data isolation, secure credential storage on GCP Secret Manager, five integration paths (Postgres, Gmail, Outlook, Google Sheets, Excel), a streaming Ask agent on LangGraph, and the Clean Agent - a human-in-the-loop data cleaning workflow with plan → execute → validate phases.

Next.js 16
React 19
TypeScript
FastAPI
Python
PostgreSQL
LangGraph
GCP Secret Manager

Read case study Visit Baza

Side Project · Live

Redline

AI contract review for non-lawyers. Upload a contract and get severity-rated red flags, verbatim citations, jurisdiction-aware checks, and a downloadable counter-proposal. Streaming keeps perceived latency under a second.

Next.js 15
React 19
LLM streaming
Tailwind v4
pdf-lib
mammoth

Read case study Open demo

Side Project · Live

Mockr

AI interview practice with structured feedback. JD-targeted or general mode, voice or typed answers, four-axis scoring rubric. Question prefetching keeps the next question instant - no waiting after feedback.

Next.js 16
React 19
TypeScript
LLM API
unpdf

Read case study Open demo

What I Bring

Full-Stack Product Engineering

Next.js, React, TypeScript on the frontend. FastAPI, Python, PostgreSQL on the backend. I own features from API design to pixel polish - including the production debugging when auth races, RLS, or streaming break at 2am.

AI-Native Product Work

Shipping LLM-powered features that hold up in production: streaming, structured outputs, agent reliability, prompt restructuring. I've built and debugged the loops, hallucinations, and edge cases tutorials don't cover.