Maahir Garg work experience. Every role, in order.

Built an internal agentic CLI agent and a sandboxed Chainlit assistant over proprietary models, with 8 custom tools, multi-agent orchestration, and skill-routing, giving an 11-person team AI tooling where classified-data constraints rule out Copilot. Engineered step-level guardrails via custom hooks that audit and validate every agent action, and designed an agentic audit pipeline that queries Snowflake and SharePoint as tools, runs ETL, and generates audit-ready reports from plain-English prompts, automating two previously manual data sources from hours to near-instant.

Co-inventor of a multimodal tracking framework (patent application in progress) for hand-eye coordination assessment in stroke rehabilitation, unifying Apple Vision Pro and iPhone into one tracking surface at 89% cross-device accuracy, 30 fps, and sub-millisecond latency (Swift, RealityKit). Ran controlled user studies with healthcare practitioners and iterated system design from empirical findings. Co-author on a research paper in preparation.

Three semesters across CS3230 (Design & Analysis of Algorithms), CS2040S (Data Structures & Algorithms), and CS1231S (Discrete Structures). Coached students through dynamic programming, graph algorithms, and complexity analysis. 4.8/5.0 teaching effectiveness rating vs 4.2 faculty average; named to the NUS Honour List of Student Tutors.

Effectively a TA for a full semester-long software-engineering project: advised 12 student teams across the whole build: architecture, implementation planning, code review, and release management. All 12 projects passed at or above their targeted grade level.

Built and optimized data pipelines against Stack Overflow under Prof. Nan Chen, modeling how feedback signals (upvotes, downvotes, acceptance rates) shape content quality over time, in support of an empirical paper.

Shipped data-driven dashboards and backend databases with Python and API integrations, lifting data accessibility across the ops team by 40%. Led SEO and performance work: 30% lift in search ranking, 25% cut in page load time, 20% growth in organic traffic.

Supported NUS IT's bug-bounty and security programme: led security projects, negotiated with vendors, and ran security-awareness training sessions for staff and peers.

Automated Google Scholar citation scraping with Python and Postman for an economics paper on a tight deadline, saving roughly 520 hours and enabling on-time publication.

Built a Python web scraper using SQLite and JWT to automate CAAQMS air-quality data collection under Prof. Nils Mattsson, eliminating over 10,000 hours of manual entry, and ran the downstream analysis.

Ran a 500+ participant AR/VR motion-sickness study in collaboration with Meta, the largest of its kind at NUS: conducted individual sessions, logged data via Python scripts and surveys, and calibrated VR headsets, informing UX improvements to Meta's headsets.