Full Product Stakeholder • Zero-Trust Agentic Architectures • Upstream Open-Source Contributor
Driving systems from zero-to-one: from formal architectural specifications and adversarial audit reports to production-grade deployment.
Profile: Full-Stack Product Architect & Senior AI Systems Engineer
Operating Mode: Sole Stakeholder (End-to-End Ownership: Concept → Spec → Audit → Build → Deploy)
Core Disciplines: Deterministic Agent Guardrails · Local Air-Gapped RAG · Multimodal Vision · Distributed Systems
Engineering Philosophy: Code-level mathematical guarantees over probabilistic LLM assumptionsThese are systems where I own the complete lifecycle as the sole stakeholder: product strategy, formal system specifications (EGM), adversarial audit reports, and production code.
1. Shaheen & IntentLock™ — Zero-Trust Agentic Execution & Escrow
- Role: Product Lead & Principal Architect (End-to-End Stakeholder)
- The Problem: Autonomous AI agents suffer from the "Checkout Cliff"—hallucinating orders, violating budget bounds, and remaining susceptible to stealth prompt-injections during live checkout.
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The Architecture:
- Cryptographic Intent Invariants: Compiles raw user intents into mathematically bounded Pydantic schemas.
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Two-Phase Financial Escrow: Integrates PayPal Sandbox v2 (
AUTHORIZE$\rightarrow$ CAPTURE). Funds are placed on programmatic hold; capture is strictly gated behind zero-trust validation. -
Deterministic Runtime Guardrails: Enforces code-level interceptors (
guardrails.py) that prevent agent self-modification or test tampering, combined with Chrome DevTools Protocol (CDP) Shadow DOM traversal. - Audit Reports & Specs: Built via the Elephant-Goldfish Model (EGM), documented through exhaustive formal design specifications and independent adversarial audit reports.
2. Multimodal RAG Pipeline — Document Intelligence Engine
- Role: System Architect & Developer
- The Architecture: Pairs dense vector retrieval with Vision-Language Models (VLMs) to process documents containing complex tabular figures, charts, and diagrams without information loss from lossy OCR/caption extraction.
3. DocuMind — Air-Gapped Local Neural RAG
- Role: System Architect & Developer
- The Architecture: A zero-telemetry, fully local personal knowledge engine powered by ChromaDB, Ollama, and cross-encoder reranking. Guarantees 100% data residency with zero external API dependencies.
4. MeetSense — Modular Audio Intelligence
- Role: System Architect & Developer
- The Architecture: Real-time audio/video ingest, diarization, speech-to-text, and conversational intelligence pipeline engineered for high-noise acoustic environments.
5. DeforestAI — Satellite Vision Monitoring
- Role: Machine Learning Engineer & Lead
- The Architecture: Computer vision segmentation network processing multi-spectral satellite imagery to identify and monitor deforestation dynamics over temporal datasets.
Beyond standalone public repositories, I have driven and delivered 15+ production feature sets across team codebases and internal platforms:
- Kanban & State Management: Architected multi-lane interactive Kanban boards with real-time state synchronization, drag-and-drop mechanics, and optimistic UI updates.
- Per-User View State & Preferences: Built persistence layers for customized filtering, sorting layouts, and saved workspace configurations.
- Permission Scoping & RBAC: Implemented role-based access control engines, tenant isolation boundaries, and cryptographic route guards.
- Secure Attachment Pipelines: Engineered authenticated file download streams, virus scanning hooks, and presigned asset delivery.
- Accessibility (a11y) Conformance: Refactored complex component trees for full WCAG/ARIA compliance, keyboard navigation focus rings, and screen-reader tree semantics.
Direct technical contributions and architectural patches to widely adopted open-source frameworks:
| Major Repository | Contribution & Subsystem | Status |
|---|---|---|
| modelcontextprotocol / servers | Model Context Protocol (MCP) Server Confinement & Isolation Engineered boundary and repository scope isolation configurations for mcp-server-git, hardening unconfined tool execution parameters for agentic context pipelines. |
Contributions 🛡️ |
| adbar / trafilatura | High-Fidelity Web & DOM Extraction Engine Contributed robust text discovery, document structure parsing, and DOM edge-case filtering routines powering downstream LLM ingestion pipelines. |
Contributions ⚡ |
| huggingface / smolagents | CPython Argument Binding in Local Python Executor Engineered standard CPython keyword/positional argument resolution for tool calling in local sandboxes. Resolved critical parameter mapping mismatches during autonomous agent execution. |
PR Shipped 🚀 |
| makenotion / notion-sdk-js | Block Schema & Column Nesting Validation Fixed child block nesting constraints allowing column_list and column structures inside single-level-nestable parent blocks across official JavaScript SDK typings. |
PR Shipped 🚀 |
| refined-github / refined-github | Deployment Visibility & Status Filtering Extended hide-inactive-deployments to intelligently prune failed and stale deployment markers across dense enterprise GitHub dashboards, improving workflow visibility for thousands of developers worldwide. |
Merged ✅ |
| tscircuit / schematic-symbols | Hardware EDA Symbol Specifications Contributed standardized phototransistor optical schematic symbol geometry and pin definitions for the open-source browser EDA circuit ecosystem. |
PR Shipped 🚀 |
Every production system I lead is developed using the Elephant-Goldfish Model (EGM), ensuring design decisions are rigorously documented and stress-tested before implementation:
- Concept Briefs (
docs/briefs/): High-level problem formulation, checkout cliff dynamics, and ROI analysis. - Formal System Specifications (
docs/designs/): Mathematical invariant definitions, Pydantic bounds, and two-phase sequence diagrams. - Adversarial Audit Reports (
docs/reviews/): Zero-context adversarial evaluations checking for prompt injection vulnerabilities, state drift, and race conditions. - Deterministic Ground-Truth Evals (
evals/): Python-based test suites validating invariant compliance and zero-trust policies under adversarial stress.
| Area | Technologies & Methods |
|---|---|
| Languages | Python (AsyncIO, AST, CPython Internals) · TypeScript · JavaScript · SQL · Bash |
| Agentic & AI | LiteLLM · LangChain · SmolAgents · Ollama · ChromaDB · Cross-Encoders · VLMs |
| Systems & Backend | FastAPI · Node.js · PostgreSQL · Redis · Docker · Chrome DevTools Protocol (CDP) |
| Frontend & UI | React 19 · Next.js · TailwindCSS · Gradio · Vite |
| Architecture | EGM Spec-Driven Development · Zero-Trust Verification · AST Interceptors · CI/CD Evals |
Engineered with deterministic rigor by Shayan Muhammad • [email protected]
Browser extension that simplifies the GitHub interface and adds useful features