Dainwi Kumar.
Systems Engineer. Rust & AI Infrastructure.
I build developer tools at the intersection of AI agent security, local-first inference, and backend infrastructure. Open to internship and full-time opportunities.
Open to internship opportunities — graduating August 2027
The "Under the Hood" Philosophy
I am a Software Engineering student focused on systems programming, AI infrastructure, and backend performance. I gravitate toward problems that sit below the application layer: securing AI agent tool calls, building local-first RAG pipelines, and designing real-time data flows. My current work centers on AgentGate — an open-source Rust proxy that intercepts and governs AI agent communication over MCP. Previously, I shipped a multi-agent research engine and a local AI code knowledge base.
- ▹Built an open-source MCP security proxy in Rust
- ▹Smart India Hackathon 2025 Qualifier
Experience
TripleHash — Full Stack Developer
- ▹Refactored legacy SQL schemas and complex joins, reducing report generation latency from 15s to 6s.
- ▹Designed and deployed a granular Role-Based Access Control (RBAC) system for multi-tenant isolation.
- ▹Automated end-to-end billing logic, eliminating manual data-entry overhead and reducing operational errors.
Featured Projects
AgentGate
Open-Source MCP Security Proxy for AI Agents
A Rust-based proxy that sits between autonomous AI agents and MCP servers, intercepting JSON-RPC 2.0 messages over stdin/stdout. Implements WAL-mode SQLite logging for full audit trails, TOML-based policy enforcement to allow/deny specific tool calls, and per-tool rate limiting via token bucket algorithm. Uses tokio::select! to handle child process lifecycle and prevent zombie processes. Phases 1–2 complete (stdio transport, logging, policy evaluation); HTTP/SSE transport and observability dashboard planned.
CodeMind
Local-First AI Code Knowledge Base
An AI-powered code knowledge base that lets developers query an entire codebase in plain English with exact file citations. Built four features: semantic vector search, RAG chat with SSE streaming, file-similarity recommendations, and an agentic Q&A pipeline that decomposes complex queries into sub-tasks. Uses a line-based chunking algorithm with configurable overlap for retrieval. Runs fully local with Ollama — zero API cost, zero data leaving the machine.
Research Agent
Multi-Agent Deep Research Engine
Transforms any query into a citation-backed research report by orchestrating a multi-agent pipeline: query expansion, web search, content scraping, LLM ranking, and synthesis — processing 15–30 sources per session. Implements concurrent page fetching via HTTPX with MD5-based deduplication. Real-time SSE streaming across the full stack.
Technical Skills
Achievements
Smart India Hackathon – Qualifier (SIH 2025)
Advanced through the SIH 2025 qualification round.
View CertificateOracle Academy – Database Design
Certification in relational database modeling and normalization (Nov 2024).
View CertificateReady to collaborate?
I'm open to internship opportunities, collaborations, and interesting projects. Let's build something together.