Archaide — Low-Latency Execution & Order Management for Multi-Asset Strategies

Results

  • Latency: <1s submit→ack
  • Uptime: 99%+ live trading
  • Ops: Faster onboarding with Zapier automation

Stack

Python, C++, JavaScript/Node, Docker, IBKR API, Alpaca REST, Zapier

TL;DR

Built and shipped equities & derivatives trading algorithms with sub-second REST integrations to Interactive Brokers and Alpaca. Designed a production OMS (Python/C++/JavaScript) with robust error handling, reconciliation, and real-time feedback loops; added risk safeguards (position limits, kill-switch, automated rollbacks). Also automated lead-capture and onboarding with Zapier to cut manual ops and boost conversion.

Context

Archaide serves multiple client strategies with different instruments, venues, and latency needs. We needed a uniform path from signal → risk checks → order routing → reconciliation while keeping tails tight during market stress.

Problem

  • Strategy code and order placement were tightly coupled, making it hard to add safeguards or swap brokers.
  • Intermittent broker API issues caused order mismatches and retries that occasionally drifted from strategy intent.
  • Onboarding new clients consumed significant manual time and slowed sales.

What I Built

  • Strategy adapters (Python) exposing a common interface for signal intake, position targets, and post-trade callbacks.
  • OMS pipeline in Python/C++ with:
  • Pre-trade risk gates: position/sector caps, notional checks, and kill-switch logic.
  • Idempotent order API with client order IDs and replay-safe retries.
  • Dual-ledger reconciliation (internal vs. broker) plus periodic position audits.
  • Real-time feedback loop to strategies (fills, rejects, price slippage, latency metrics).
  • Broker adapters for Interactive Brokers and Alpaca using sub-second REST calls; standardized error taxonomy and backoff.
  • Go-to-market ops: Zapier flows wiring forms → CRM → email/messaging → doc-sign → account-creation checklist; auto-provisioned dashboards for new clients.

Architecture (high level)

Strategies → Risk Gate → Order Router/OMS → Broker Adapters (IBKR/Alpaca)

Key Decisions

  • Separate risk gate before any network calls → consistent enforcement and simpler testing.
  • Replay-safe IDs so retries never double-fill.
  • Standardized error taxonomy across brokers → simpler alerting and SLOs.
  • Periodic reconciliations (positions, cash, fills) to catch silent drifts.

What I’d Do Next

  • Add FIX or websocket-native routes (where available) to shave latency variance.
  • Shadow orders / canary per strategy before rollout.
  • Latency budgets per stage with automated budget regression tests.
  • Bracket/OCO templating to simplify complex exits.