Systems engineering for software that has to hold up under real traffic.

Performance & runtime

Profile the hot paths, move the right ones to native code, fix memory layout and allocation behavior, and bring down p95 latency and request volume.

Distributed systems & async Rust

Peer-to-peer sync, request/response protocols, timeouts and backpressure, per-peer retry and feature detection, and the transport observability to see what is actually happening.

Production reliability & forensics

Diagnose deadlocks, async stalls, and runaway memory under real load with thread stacks, futex waits, and dump hooks. Then ship the fix, the watchdog, and a test that reproduces the failure.

Runtime, VM & compiler

Custom VM and C-runtime integration, compiler and interpreter parity, single-allocation deserialization, memory-mapped state, and native fast paths that match the reference exactly.

AI agent & evaluation infrastructure

Long-running agent harnesses, supervisors and heartbeat checks, append-only event buses, multi-model fan-out, and grading by reference and differential checks.

Technical due diligence

Code, architecture, dependencies, delivery risk, security posture, and execution quality, returned as clear written tradeoffs.

1. Zorpproduction blockchain node · Rust

   • p95 164ms → 66ms, requests −61%: reworked peer-to-peer sync to fetch a block with its transactions across mixed-version peers, measured with a deterministic A/B harness.
   • state migration 385s → 91s: memoized repeated tree walks; exported state hashed bit-for-bit identical against production checkpoints.
   • async stalls resolved: traced to overloaded responders, fixed with bounded queues and watchdogs, plus a stress harness that reproduces it.

2. TlonVere, Urbit's C runtime

   • Built the khan and conn IPC drivers and the noun wire protocol across the kernel/runtime line; batched event-log replay on the boot path; wrote Nock jets matched exactly to the interpreter.

3. VaporwareUrbit / Hoon backend

   • Token-gated software distribution: a chain-log scanner, an ERC-1155 and account-event parser, an ownership store, and an update stream for the apps on top.

4. EarlierML & data systems

   • Fraud-detection ML in production at Feedzai; Elixir/Erlang healthcare data at Cota; Scala/Spark data platforms at Owl Analytics, Bank of America, and Morgan Stanley.

• Direct technical diagnosis: what is actually wrong, not what is easiest to say.
• Clear written tradeoffs you can act on.
• Changes verified against a reference: differential runs, deterministic A/B, bit-identical state hashes where it matters.
• Focused delivery on agreed scope.
• Handoff notes that make the next operator's job easier.

Email hello@rayder.systems with a short description of the system and the problem in front of you.