I work at the intersection of Applied AI and security engineering — red teaming and building controls for production AI systems at my workplace before they reach end users. Traditional security reviews don't cut it for AI. My job is to find the things that change deployment decisions.
What I'm working on:
- Engineered a firm-wide Gen AI Red Teaming platform enabling systematic automated and manual adversarial evaluation of LLM use cases across all lines of business
- Led the red team assessment of flagship LLMs, surfacing multiple critical and high-severity vulnerabilities — prompt injection, data leakage, system prompt extraction, and intent drift — before the models reached production
- Authored a blueprint for Advanced Manual Red Teaming: a structured methodology for uncovering behavioral vulnerabilities and intent misalignment that automated scanners fundamentally cannot detect
- Architected a Network Broker enabling secure, isolated connectivity between internal red teaming platform and external vendor evaluation infrastructure
- Containerized and deployed Red Teaming ECS Task modules for concurrent adversarial evaluation of multiple AI use cases without capacity constraints
- Reviewed emerging AI coding tools from a security perspective, producing key findings that directly shaped firm-wide decisions on AI coding enablement
- Building AI Controls engineering solutions to systematically enforce safety, scope, and behavioural boundaries across deployed LLM use cases
Recognition: Inventor Recognition (Q4 2025) for filed patents · Speaker at DEVUP 2026 (my workplace's invite-only technical conference) · SEP Engineer Committee Lead for 1,100+ early-career engineers at my workplace Bengaluru Tech Centre
These are full-fledged engineering projects built to address critical, high-risk security and simulation challenges at the frontier of AI and biological computing.
Organoid Intelligence (OI) Biocomputer Simulator A scientifically rigorous interactive web dashboard simulating an organoid biocomputer lab, running living human brain cells on silicon chips. Grounded in peer-reviewed research (Nature & Frontiers).
| Interactive AI Security Hacking Playground A gamified Capture The Flag platform designed to teach hands-on adversarial thinking. Mapped directly to real-world risk frameworks (OWASP LLM Top 10 & MITRE ATLAS).
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AI Scope & Intent Enforcement Proxy Gateway An enterprise-grade safety proxy and automated red-teaming tool designed to keep deployed LLM applications safe, secure, and strictly aligned within their defined scopes.
🔒 Stealth / Private Repository | Absolute Safety Robustness Evaluation Harness An advanced LLM safety benchmark that evaluates absolute, severity-weighted category failure rates instead of shifting, relative statistics (Z-scores).
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prompt-injection-ctf (⭐ 2) — Interactive AI Security Playground — Prompt Injection CTF. Craft attack prompts to break constrained AI systems. Learn prompt injection, jailbreaking, intent drift & token smuggling. Built to teach adversarial thinking hands-on.
ai-security-resources (⭐ 2) — Curated directory of state-of-the-art Adversarial AI Security tools, vulnerability scanners, safety benchmarks, guardrails, and compliance standards.
weighted-safety-refusal (⭐ 1) — Severity-weighted LLM safety evaluation suite. Measures absolute refusal robustness across prompt injection, jailbreaking, data exfiltration, toxicity, and malware generation using risk-adjusted weights.
llm-ops-workshop — End-to-end MLOps workflow demonstrating model lifecycle, monitoring, and deployment practices.
synaptic-wetware — 🧠 Organoid Intelligence Biocomputer Simulator — HH + Izhikevich neuron models, MEA burst detection, DishBrain Pong, Baltimore Declaration ethics monitor. Built by Antigravity (Google DeepMind).
Also building something in AI security — stealth mode 🔒
📋 Full list of external contributions — repos outside my account where I've contributed (2020–present)
LLMs & AI Platforms
Red Team & Security Tools
Frameworks & Standards
Tech Stack
