Remote: Yes, remote-first (open to work in any timezone, comfortable working async with distributed teams)
Willing to relocate: Yes
Technologies: TypeScript, Rust, C#/.NET, distributed systems, network protocols (gRPC, binary transports, REST), Model Context Protocol (MCP), ZK (Groth16 on BLS12-381, Arkworks, RISC Zero zkVM)
Résumé/CV: https://github.com/Dyslex7c
Email: ritsphs@gmail.com
Final-year CS student (graduating mid-2027) working on distributed systems, network protocols, and AI agent infrastructure. Looking for remote roles in AI/ML systems, agent runtimes, or distributed backend/protocol engineering. Open to work across any timezone.
Recent work:
- Spigot: Building an HTTP per-call micro-billing gateway and Model Context Protocol (MCP) server for autonomous AI agents, handling tool call authorization, atomic ledgering, and idempotency.
- Nethermind (Ethereum runtime client, C#): did an SWE internship (Mar-Jun 2026), and worked on Pureth (trustless log and state indexing engine). Implemented witness capture endpoints and built an SSZ-REST binary transport that cut latency by 4.8x over JSON-RPC. Also led a type-unification refactor (`long`/`UInt256` to `ulong`) across ~1300 files reviewed by core engineers, and fixed failing state-transition specification tests.
- Grandine (Rust consensus client): integrated the Ziren zkVM into Grandine (merged PR #385) for off-chain execution verification.
- LayerEdge (SDE intern, Singapore): built a RISC Zero zkVM-backed Rust service and Merkle-tree state-change detection to cut redundant ZK proof verification.
- cadas-core (Rust research prototype): DispersedSimplex BFT consensus with FRIDA erasure coding, fault-injection simulation, and byte-level network metrics.
- ZK from scratch: Groth16 zk-SNARK on BLS12-381 (Arkworks); Chaum-Pedersen ZKP gRPC system in Rust with Miller-Rabin prime generation and Fiat-Shamir.
Also contributed to Reth, Besu, Ream, Forest, and distributed telemetry tooling. Won the Unfold 2024 hackathon Bullieverse AI Agent track.
Looking for opportunities in the AI/ML space (AI agent infrastructure, MCP tool execution, runtime systems), distributed systems, zkVMs, and consensus/protocol engineering. I like turning specs into working code and finding spec-vs-implementation bugs.