Staff Software Engineer

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Startup Talent

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2014

🎯 Recrutamento

👥 RH Tech

🤝 B2B

Recruitment • HR Tech • B2B

A Startup Talent é uma empresa de recrutamento especializada em conectar empregadores com talentos de ponta em diversos setores. Eles se concentram em ajudar empresas a construir equipes sólidas e alcançar seus objetivos de recrutamento, atraindo candidatos relevantes e retendo funcionários. A Startup Talent enfatiza sua expertise em setores como TI, tecnologia e vendas, fornecendo soluções personalizadas de recrutamento adequadas a uma variedade de padrões de trabalho e tipos de emprego.

Descrição

• 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.

🎯 Requisitos

• 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)

🏖️ Benefícios

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