Descripción de la oferta
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 / Beneficiosbase salary plus potential bonusstock options40% discount on Fever eventshome office-friendlyhealth insuranceflexible remuneration via Cobee
ResponsabilidadesBuild and improve the agentic harness: skills, sub-agents, guardrails, tools, and verification for high-quality outputDevelop a shared knowledge-base substrate that compounds across FeverOwn the delivery substrate and autonomous rails: cloud environments, CI runtime, ephemeral environments, migration toolingShape AI usage across a squad’s workflows, tooling, and coordination to reduce frictionCreate evaluation and measurement infrastructure with baselines and metrics that matterOptimize inference economics: model routing, prompt caching, and cost-aware decision makingDrive real adoption by ensuring tools are used effectively by squadsMaintain engineering excellence: testing, patterns, CI/CD, observabilityEnsure end-to-end production ownership and live-issue accountability
Requisitos principales5+ years building and operating production software at meaningful scaleStrong software design fundamentals: testing, design patterns, clean architectureBackend depth: RESTful APIs, relational databases, async/event-driven patternsEnd-to-end production ownership: CI/CD, observability, infrastructure, live performanceProficient in business English1–2 years+ deep in LLM applications shipped to production with context engineering, RAG, multi-agent systemsAuthored skills, sub-agents, evals, and verification harnesses in agents and can explain implementationAbility to measure and conduct controlled experiments to prove improvementsownershipcollaboration across squadsresults-orientedRESTful APIsRelational databases and SQLDistributed/async patterns (queues, messaging)
