Overview La información a continuación detalla los requisitos del puesto, la experiencia esperada del candidato y las cualificaciones correspondientes.

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 xugodme 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 (Murcia)
🏢 MindMatch
📍 Murcia