# Chandra Prakash S - Complete Profile & Engineering Knowledge Base

Domain: https://www.chandraprakashs.im
Email: chandra.1997@hotmail.com
Phone: +91-7780711026
Location: Bengaluru, India
Status: Open to Opportunities
GitHub: https://github.com/leviathanaxeislit
LinkedIn: https://linkedin.com/in/chandra-prakash-s

---

## About & Engineering Philosophy
Software Engineer (ex-ClarityUX) building production-grade AI systems, Conversational AI, Generative AI tools, multi-provider LLM orchestration, and low-latency infrastructure born from real friction.

> "Technology is a means; the product is the outcome. Simplicity is sophistication. Engineering should disappear—users shouldn't notice architecture or AI complexity, only that it feels effortless."

---

## Education
- **Master of Computer Applications (MCA)**
  - Institution: Dr. M.G.R Educational and Research Institute
  - CGPA: 8.05
  - Focus: Advanced computer science fundamentals, machine learning architecture, distributed backend systems.
- **Bachelor of Science in Computer Science (B.Sc. CS)**
  - Institution: SRM Institute of Science and Technology
  - CGPA: 8.6

---

## Deep Tech Projects & Work History

### 1. ClarityUX — Multi-Provider AI Inference & Visual Attention Analytics
- **Role**: Software Engineer (ClarityUX)
- **Category**: AI Vision & LLM Orchestration
- **Problem**: Production AI workflows often suffer from vendor lock-in, latency bottlenecks, and subjective UI review iterations lacking empirical visual attention data.
- **Solution**: Architected a multi-provider inference system integrating Gemini, Claude, Groq, and OpenAI alongside OpenCV/FastAPI computer vision pipelines for predictive heatmaps, attention hotspots, and eye-path simulations across Figma plugins, Chrome extension, and Next.js platforms. Shipped production Conversational AI systems, Generative AI workflows, and real-time user feedback systems.
- **Key Metrics & Achievements**:
  - 40% reduction in UX analysis turnaround time.
  - Serving 4,000+ active users globally across Figma & Chrome.
  - Engineered Conversational AI assistants & Generative AI UI synthesis features.
  - Built real-time user feedback system for continuous UX evaluation & iteration.
  - 30% reduction in backend bottlenecks with Node.js inference pipeline.
- **Tech Stack**: Conversational AI, Generative AI, Feedback System, Python, FastAPI, OpenCV, TensorFlow, React, Next.js, LiveKit.

### 2. AI Workforce Planning (Altruisty) — Dual-Sided Workforce Intelligence
- **Role**: ML & Systems Architect (Altruisty)
- **Category**: Generative AI, Recommendation Systems & Vector Search
- **Problem**: High-volume hiring pipelines suffer from mismatched candidate recommendations, manual resume evaluations, and fragmented recruiter outreach, while candidates lack tailored career insights and instant guidance.
- **Solution**: Architected a dual-sided workforce intelligence platform. Built initial POCs utilizing PyTorch, TensorFlow, and Collaborative Filtering models before scaling to production with Gemini Embeddings and Firestore Vector Search. For recruiters, provided semantic resume matching, KB role auto-JD generation, candidate Kanban board, and cold message email dispatch. For candidates, engineered a role recommendation portal providing salary/career path insights, ATS resume builder, cover letter generation, and a companion Telegram bot for mobile assistance.
- **Key Metrics & Achievements**:
  - Architected POC models using PyTorch, TensorFlow & Collaborative Filtering before migrating to production Gemini Embeddings.
  - Recruiter Dashboard: Firestore Vector Search for semantic resume ranking, role KB auto-JD generator & interactive Candidate Kanban.
  - Candidate Portal: Personalized role recommendations with salary benchmarks, career path insights & tailored job discovery.
  - AI Career Copilot & Telegram Companion Bot: Auto-generates ATS resumes, cover letters, and provides mobile candidate assistant alerts.
  - Recruiter Outreach: Gemini cold message template synthesis with direct-from-dashboard candidate email dispatch.
- **Tech Stack**: Gemini API, Gemini Embeddings, Firestore Vector Search, Telegram Bot Companion, PyTorch, TensorFlow, Collaborative Filtering, Python, Next.js, ATS Resume Builder, Recruiter Kanban.

### 3. Sunflower AI — Multi-Modal Spatial & Video Intelligence
- **Role**: Creator & Lead Developer
- **Category**: Real-Time Vision & Edge Computing
- **Problem**: Edge thermal vision and multi-modal video feeds frequently suffer from high frame drop rates and false positive detections in complex environmental conditions.
- **Solution**: Implemented a spatial video analytics server with real-time bounding box projection, thermal object tracking, and automated alert dispatch using OpenCV and custom edge ML pipelines.
- **Tech Stack**: OpenCV, Python, PyTorch, Edge AI, WebSocket, WebRTC.

---

## Published Technical Articles & Case Studies

### 1. Building Multi-Provider AI Inference Systems
- **Summary**: Technical breakdown of architecting failover mechanisms, latency optimization, and unified prompt interfaces across OpenAI, Anthropic, Gemini, and Groq.
- **Topics**: System Design, LLM Routing, Fallback Engineering, Low-Latency APIs.

### 2. Real-Time Visual Attention Modeling with OpenCV & FastAPI
- **Summary**: Engineering predictive gaze heatmaps and attention density scoring using classical computer vision algorithms integrated into web applications.
- **Topics**: Computer Vision, OpenCV, FastAPI, Async Python, Image Processing.

---

## Machine-Readable API Summary
For programmatic query or LLM agent tool integration:
- JSON API: https://www.chandraprakashs.im/api/agent
- Dynamic Sitemap: https://www.chandraprakashs.im/sitemap.xml