Overview In Fever’s AI & DevEx squad, you will shape production-grade AI-powered software that accelerates the entire Product Engineering org. You’ll own end-to-end delivery across agent harness, knowledge base, and autonomous delivery rails, with strong emphasis on testing and observability. You’ll partner with squads to ship impactful AI-enabled workflows at scale. This is a chance to influence how AI augments engineering and delivery across Fever. Compensaciones / Beneficios * base salary plus potential bonus * stock options * 40% discount on Fever events * home office-friendly * health insurance * versátil remuneration via Cobee Responsabilidades * Build and improve the agentic harness: skills, sub-agents, guardrails, tools, and verification for high-quality output * Develop a shared knowledge-base substrate that compounds across Fever * Own the delivery substrate and autonomous rails: cloud environments, CI runtime, ephemeral environments, migration tooling * Shape AI usage across a squad’s workflows, tooling, and coordination to reduce friction * Create evaluation and measurement infrastructure with baselines and metrics that matter * Optimize inference economics: model routing, prompt caching,



and cost-aware decision making * Drive real adoption by ensuring tools are used effectively by squads * Maintain engineering excellence: testing, patterns, CI/CD, observability * Ensure end-to-end production ownership and live-issue accountability Requisitos principales * 5+ years building and operating production software at meaningful scale * Strong software design fundamentals: testing, design patterns, clean architecture * Backend depth: RESTful APIs, relational databases, async/event-driven patterns * End-to-end production ownership: CI/CD, observability, infrastructure, live performance * Proficient in business English * 1–2 years+ deep in LLM applications shipped to production with context engineering, RAG, multi-agent systems * Authored skills, sub-agents, evals, and verification harnesses in agents and can explain implementation * Ability to measure and conduct controlled experiments to prove improvements * ownership * collaboration across squads * results-oriented * RESTful APIs * Relational databases and SQL * Distributed/async patterns (queues, messaging)

📌 AI Staff Engineer (Córdoba)
🏢 Fever
📍 Córdoba