I am an Artificial Intelligence and Machine Learning engineering student focused on building dependable software products that combine AI engineering, full-stack development, system design, and product thinking.
My recent work includes real-time assessment monitoring, Agentic AI workflows, retrieval-augmented generation, local LLM integration, backend APIs, developer tooling, and deployment-oriented engineering. I prefer building complete systems rather than isolated model demonstrations.
- Maintainable architecture and clear separation of concerns
- Secure APIs, policy enforcement, auditability, and controlled automation
- Reliable AI integration with validation and human approval boundaries
- Responsive interfaces and practical end-to-end workflows
- Testing, CI/CD, version control, and deployment readiness
- Software Engineering Internships
- AI/ML Engineering Opportunities
- Full-Stack Product Development
- Agentic AI and RAG Projects
- Open-Source Collaboration
- Hackathons and Research Prototypes
| Domain | Level | Practical Experience |
|---|---|---|
| Agentic AI Systems | Advanced | Multi-agent workflows, tool calling, policy-driven execution, task planning, and approval loops |
| Large Language Models | Advanced | Prompt engineering, Ollama, Transformers, local open-source models, and response orchestration |
| Retrieval-Augmented Generation | Advanced | ChromaDB, vector search, document retrieval, embeddings, and grounded generation |
| Computer Vision | Intermediate | OpenCV, image processing, edge detection, segmentation, screen monitoring, and evidence capture |
| Natural Language Processing | Intermediate | Text extraction, classification, intent detection, prioritisation, and information retrieval |
| AI Product Engineering | Advanced | AI APIs, frontend workflows, testing, deployment, and observability |
| MLOps | Intermediate | CI/CD, reproducible environments, validation, monitoring, and release workflows |
LiveLook-V2 - AI-Powered Real-Time Assessment Monitoring
A real-time platform for monitoring online assessments and laboratory sessions through live screen streaming, policy enforcement, evidence capture, risk detection, and faculty-focused workflows.
| Category | Details |
|---|---|
| Stack | FastAPI, WebSockets, Next.js, React, Python, MSS, psutil, pywin32, SQLite |
| Architecture | Student agent, backend API, WebSocket streaming layer, policy engine, and teacher dashboard |
| Core Features | Active-window tracking, blocked-application detection, evidence capture, alerts, and live monitoring |
| Engineering Focus | Modular services, low-latency communication, auditability, testing, and CI/CD |
| Repository | View LiveLook-V2 |
- Designed and implemented major parts of the Windows student monitoring agent.
- Integrated screen capture, active-window detection, application monitoring, and WebSocket communication.
- Coordinated backend, frontend, and agent integration through Git branches and shared API contracts.
- Defined session policies, evidence workflows, and risk-based monitoring behaviour.
AI Lab Record Generator - Agentic Academic Automation
An AI-assisted platform for converting experiment observations and structured inputs into formatted academic laboratory records using Django, OCR, RAG, LLM workflows, and document generation.
| Category | Details |
|---|---|
| Stack | Django, Python, OCR, Ollama, RAG, ChromaDB, Next.js |
| Pipeline | Upload, extraction, retrieval, generation, validation, formatting, and PDF export |
| Architecture | Modular Django applications for documents, experiments, accounts, APIs, and agents |
| Engineering Focus | Structured data models, testing, retrieval quality, validation, and document consistency |
| Repository | View AI-Lab-Record-Generator |
- Designed the Django backend structure and experiment data model.
- Built workflows for observation upload, retrieval, record generation, and validation.
- Integrated ChromaDB-based retrieval and local LLM tooling.
- Defined unit, integration, and end-to-end testing requirements.
Medical Care Centre - Open-Source AI Healthcare Assistant
An AI-powered healthcare assistant prototype that supports medical queries, contextual responses, and emergency-oriented routing using open-source language models and FastAPI services.
| Category | Details |
|---|---|
| Stack | Python, FastAPI, React, Transformers, TinyLlama, Ollama |
| Core Features | Medical chatbot, contextual response flow, emergency triage concepts, and API integration |
| Engineering Focus | Local model integration, structured prompts, response quality, and frontend-backend communication |
| Repository | View Medical_Care_Centre |
- Integrated an open-source LLM into a healthcare-focused chatbot workflow.
- Developed backend APIs and frontend-agent communication.
- Evaluated response quality, context limits, and model behaviour.
- Planned RAG, speech, and doctor-availability extensions.
LiveLook-V2 - AI Assessment Monitoring Platform
2026 - Present
- Coordinating a small development team across backend, frontend, and Windows-agent responsibilities.
- Defining Git branches, integration milestones, API contracts, and prototype scope.
- Implementing monitoring features including screen streaming, active-window tracking, evidence capture, and live events.
- Supporting testing, deployment planning, and production-readiness improvements.
AI Lab Record Generator
2026 - Present
- Developing a document automation workflow using Django, OCR, RAG, local LLMs, and PDF generation.
- Building modular components for retrieval, generation, validation, and formatting.
- Maintaining Git history, resolving integration conflicts, and improving test coverage.
| Recognition | Details |
|---|---|
| AI Agents Intensive Programme | Completed a five-day programme covering agents, multi-agent systems, prompt engineering, tool calling, application development, and deployment |
| Hackathon Product Leadership | Led rapid product planning and technical execution for AI monitoring and automation prototypes |
| Real-Time Monitoring Architecture | Designed a screen-streaming and risk-detection workflow using WebSockets, policies, and evidence capture |
| Open-Source LLM Integration | Worked with TinyLlama, Qwen, Ollama, and Transformers in practical applications |
| Collaborative Engineering | Applied branching, rebasing, conflict resolution, modular ownership, and CI/CD practices |
learning:
- Advanced Agentic AI architectures
- Retrieval-Augmented Generation
- Production MLOps workflows
- Secure distributed systems
building:
- Real-time assessment monitoring
- Agentic academic automation
- AI-powered full-stack applications
exploring:
- Multi-agent collaboration
- Local open-source LLM deployment
- AI evaluation and observability
- Human-in-the-loop automation
open_to:
- Software engineering internships
- AI and machine learning roles
- Full-stack product engineering
- Open-source collaboration
