Software Engineer Backend DevOps

This is a remote position.
The company is an OnchainGPT for autonomous trading. It is an AI-powered mentor, advisor, and companion that helps users explore the onchain world, find alpha, auto-trade, and outsmart the market.

They are looking for Staff Software Engineer (Backend and AI Infra) who will own two critical workstreams :

- and the migration of model hosting and agent deployment in-house, moving the company off third-party LLM providers and hosted agent platforms to own infrastructure.

NOTE : This role is NOT a pure Devops role but rather a building role in which you will spend 80% of your time writing Go, Python, and TypeScript that ships to production.

You are in charge of managing the very infrastructure you are building, as its designer you are be the best person to operate it.

This is foundational infrastructure for a new category of software.

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; Scanner Gateway / Rules Engine — a YAML-configurable evaluation layer that sits between scanners and execution. Scanners produce raw signal variables; Users customize trading behavior without touching Python. 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. 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. Model hosting — evaluate and implement the path from external LLM APIs (Anthropic, Google) to self-hosted inference. Agent telemetry — capture every scanner evaluation, every trade decision, every signal score across all agents. This data feeds the self-reinforcing loop: agents learn from fleet-wide performance, fork winning strategies, and improve autonomously

Deployment pipeline — CI/CD for shipping scanner updates, runtime patches, and skill configs to 50+ live agents without interrupting open positions. Own incident response — in a trading system, every minute of downtime is real dollars at risk

Health monitoring for the agent fleet: which agents are scanning, which are stuck, which have the midnight rollover bug

Strong backend engineering — you write production code daily in at least two of: Go, Python, Node.js/TypeScript. Experience building backend services from scratch at a startup: 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)
Background in trading systems, exchange APIs, or fintech where uptime has direct financial consequences
Experience with CI/CD for systems where “deploy” means updating live trading agents, not just web servers

Benefits

Permanent role - Remote EU or US
Benefits: healthcare and life insurance, retirement plan, sponsored transportation, gym, lunch card, home office equipment, and other perks.
Video call with CEO/CTO (30mn).