Backend Engineer Needed: Sub-1-Second Caching, Pricing Algorithm & UI Polish (React Native / Node.js

⚠️ CRITICAL NOTICE BEFORE APPLYING: The budget and milestones for this MVP stabilization phase are fixed at $500 and are completely non-negotiable. We are looking for a focused, elite developer—not a corporate agency looking to over-scope or up-sell us. Payment is strictly tied to real-world performance metrics. Milestone 1 requires a live mobile stopwatch test showing sub-1-second cache loading on repeat lookups. We measure deliverables with a stopwatch, not excuses. If you do not have deep experience with high-speed backend architecture and caching models, please do not apply. 🚀 The Long-Term Equity & Full-Time Vision: While this initial stabilization phase is a compact $500 MVP project, we are actively scouting for our long-term technical partner. The engineer who successfully executes this phase and cracks our speed bottleneck will have the first right of refusal for a permanent, full-time position as our Lead Developer. You will spearhead the architecture for the entire upcoming Reseller Bro Ecosystem, which includes building out our dedicated social media features, rolling out full business-to-business (B2B) cross-platform inventory management tools, and leading our upcoming wearable AR glasses workflow ("Bro Lens"). www.resellerbro.com Project Overview: Please note: This application is approximately 80% complete. The front-end user interface, layout screens, and navigation are already fully built out. We are not asking you to build an app from scratch. We need an expert developer to step in and handle the final 20% of the project: cleaning up our database cache to hit our performance targets, implementing a tier-condition formula, handling minor UI adjustments, and adding high-energy audio/vibration triggers. IReseller Bro is a powerful mobile utility application designed for on-the-go resellers to instantly analyze product values, get a FLIP/SKIP verdict, and SAVE to a digital cart in seconds. We are anchoring our backend data pipeline to a high-speed eBay API model that automatically calculates smart market estimates for other secondary platforms. The Core Tasks & Milestone Payment Structure: 🔹 Milestone 1: Sub-1-Second Centralized Caching ($100 Escrow) The Issue: The previous build incorrectly forced live AI image recognition to run on every single scan, causing a painful 7–8 second delay even on repeat lookups. The Fix: You must implement a proper, high-speed database caching layer. The first initial scan of a brand-new item can take up to 7 seconds to run the AI workflow and fetch external marketplace data. However, on any repeat scan by any user, the app must bypass the AI image recognition entirely, read a cached unique identifier, and pull the results from the database instantly in under 1 second. 🔹 Milestone 2: Data Engine & Percentage-Based Estimation Matrix ($200 Escrow) The Fix: Connect the backend cleanly with the official eBay Browse API using our developer keys. Target Marketplaces: The app displays valuation metrics for four core platforms: eBay, Depop, Grailed, and Poshmark. Condition Matrix & Platform Estimation Formula: Build an automated mapping matrix. The app will pull raw condition data from the eBay API, group it cleanly into our 3-tier user system, and use those baselines to calculate estimated values for the other platforms using an internal multiplier matrix. New Tier: Maps: "New", "Excellent", "Excellent - Refurbished", "Open box", "New with box", "New with defects", and "New without box". Good Tier: Maps: "Very Good", "Good", "Used", "Very Good - Refurbished", "Good - Refurbished", "Pre-Owned", and "Certified Pre-Owned". Poor Tier: Maps heavy-wear options directly ("For parts or not working" or "Fair"). If a specific item category lacks a true "poor" marketplace data option, the engine must automatically fall back to calculate a custom percentage markdown (e.g., 40% less) relative to that item's "Good" tier baseline. Smart Category Specifications (Vehicle & Electronics Handling): If the AI detects an image of a Vehicle or high-value Electronics, the app must dynamically generate a quick-spec form for the user to confirm/fill in (Vehicles: Make, Model, Year, Mileage; Electronics: Brand, Model, Capacity) to feed directly into the pricing API for precise accuracy. 🔹 Milestone 3: UI Redesigns, Audio/Haptics, Live Deployment & Final Handoff ($200 Escrow) UI Tweaks: Implement minor visual layout edits and updates to a few existing UI screens to align with this new calculation model. This includes ensuring tiles are accurately labeled as "Estimated Value," verifying the condition buttons display perfectly, adjusting the selling platform logos/designs, and making a few structural changes to the "Saved Items" page. Haptics & Custom Audio Cues: Implement device vibration triggers (via Web Vibrations API) to pulse the device exactly when a verdict hits the screen. Integrate custom short audio sound bites that trigger instantly on the verdict display: a high-energy "YEAH!" (Lil Jon style) sound bite for a FLIP verdict, and a "HELL NO!" sound bite for a SKIP verdict. “ Live Deployment & Handoff: Successfully deploy the production build live onto our hosting account so the application is fully operational. Clean up the codebase and hand over the complete, finalized source repository. Requirements: Deep expertise in backend optimization, API data pipelines, and high-speed database caching. Proficiency in mobile development frameworks (React Native), front-end audio integration, and Node.js/Python. Strong communication skills. You will work with an existing repository and must provide clean, documented code. To Apply: Please reply with the word "LAUNCH" at the top of your cover letter so I know you read the full description. Explain exactly how you will structure the database cache so that a repeat scan completely bypasses the image-recognition API step to hit the sub-1-second mark globally.