The runtime is the engine that makes every agent work. You’ll own the core systems: Plugin Runtime — the per-agent process that runs position tracking (10s polling), the RatchetStop exit engine (tiered trailing stops with sub-second evaluation), and DSL state management.
Currently Go + Python; migrating to a centralized Go service with Postgres state and real-time websocket price feeds
Scanner Gateway / Rules Engine — a YAML-configurable evaluation layer that sits between scanners and execution.
Scanners produce raw signal variables; the rules engine applies gates, scoring, and filters defined in YAML. Users customize trading behavior without touching Python. This is the next major runtime feature RatchetStop
Backend — centralized profit-trailing service that protects positions even when the agent is offline. Evaluates tier upgrades and places stop-loss orders on Hyperliquid via websocket, replacing per-agent polling with condition-based evaluation across all positions
Execution Layer — the MCP (Model Context Protocol) server that bridges agents to the company's 48+ platform tools: position creation, clearinghouse state, market data, Smart Money intelligence.
You’ll own auth, rate limiting, and the contract between agents and the exchange
Data Layer — enriched Hyperfeed pipeline (top 1K trader positions, momentum events, market concentration) flowing through Redis, Postgres, and ClickHouse. Real-time ingestion, 4-hour rolling windows, and the APIs that every scanner calls
The company is moving off third-party hosted agents and external LLM inference to the company's owned infrastructure. You’ll lead the technical execution: Agent deployment platform — migrate agents from Railway/OpenClaw to own-hosted infrastructure.
Each agent needs isolated workspace, cron scheduling, state persistence, MCP connectivity, and Telegram notifications. Target: deploy any skill from a GitHub repo with one command
Model hosting — evaluate and implement the path from external LLM APIs (Anthropic, Google) to self-hosted inference. Options range from proxied external models with full telemetry capture, to fine-tuned models running on own GPUs.

Requirements

Strong backend engineering — you write production code daily in at least two of: Go, Python, Node.js/TypeScript. Go being the preferred language for the runtime services
Experience building backend services from scratch at a startup: APIs, job scheduling, state management, distributed systems
Solid understanding of real-time systems where latency matters: websocket connections, condition-based evaluation, sub-second response requirements
Production experience with Postgres, Redis, and at least one analytics DB (ClickHouse, TimescaleDB, BigQuery)
Kubernetes experience — deploying, scaling, and debugging production workloads on AWS EKS
You’ve owned a system end-to-end: designed it, built it, deployed it, operated it, fixed it at 3am
Experience with model serving / LLM infrastructure — deploying, scaling, and optimizing inference (vLLM, TGI, TensorRT-LLM, or managed endpoints) (strong plus)
Background in trading systems, exchange APIs, or fintech where uptime has direct financial consequences (strong plus)
Experience with onchain infrastructure: wallet operations, RPC nodes, transaction monitoring, DEX integration (strong plus)
Familiarity with MCP (Model Context Protocol) or similar agent-to-tool connectivity patterns (strong plus)
Experience building multi-agent platforms — orchestrating many independent processes sharing infrastructure but operating autonomously (strong plus)
Experience with CI/CD for systems where “deploy” means updating live trading agents, not just web servers (strong plus)

Benefits

healthcare and life insurance
retirement plan
sponsored transportation
gym
lunch card
home office equipment
other perks

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

GoPythonNode.jsTypeScriptPostgresRedisClickHouseKuberneteswebsocketLLM infrastructure

Soft Skills

backend engineeringsystem designproblem-solvingownershipcollaborationscalabilitydebuggingoperational excellenceadaptabilitycommunication