Senior Software Engineer - AI Agents & Developer Platform

Hey there!

We're Fever, the world's leading tech platform for culture and live entertainment.

Our mission? To democratize access to culture and entertainment. With our proprietary cutting‑edge technology and data‑driven approach, we're revolutionizing the way people engage with live entertainment.

Every month, our platform inspires over 300 million people in +55 countries (and counting) to discover unforgettable experiences while also empowering event creators with our data and technology, helping them scale, innovate, and enhance their events to reach new audiences.

Our results? We've teamed up with major industry leaders like Netflix, F.C. Barcelona, and Primavera Sound, presented international award‑winning experiences, and are backed by several leading global investors! Impressive, right?

To achieve our mission, we are looking for bar‑raisers with a hands‑on mindset who are eager to help shape the future of entertainment!

Ready to be part of the experience?

Now, let's discuss this role and what you will do to help achieve Fever's mission.

We're building the team that defines how AI transforms Product Engineering s is a backend engineering role first: you need strong software fundamentals to build systems that scale and hold up in production. The AI expertise builds on top of that foundation. You won't just use agents, you'll build the harnesses, evals, and infrastructure that make them ship reliable, high‑quality output across the entire company.

You'll join the AI & Dev Ex team. Our mission is to raise the performance of Fever's whole Product Engineering organization, not just individual engineers, but entire squads (product, design, and engineering together) and everything that surrounds their work: CI/CD, observability, infrastructure, data, and how people communicate and coordinate. We look for the highest‑leverage points in that chain and build AI‑powered tools to improve them, always backed by measurement, not assumptions.

• Agentic harness:
  Build the skills, sub‑agents, guardrails, and verification systems that make agents produce high‑quality, trustworthy output, for engineering and beyond.
• Knowledge base:
  Build the shared knowledge substrate agents read from and write into, growing it from team‑level to something that compounds across all of Fever.
• Delivery substrate:
  Own the cloud dev environments, CI runtime, and autonomous‑delivery rails that turn a request into an environment, an agent run, and a reviewable pull request. You're responsible for how fast and reliably this works.
• AI across how squads work:
  Go beyond coding agents. Find where AI removes friction in planning, coordination, and communication across a squad's daily work.
• Measurement:
  Build the evaluation and metrics systems (baselines, before/after comparisons, DORA metrics, lead time, real adoption) that ensure every change ships on signal, not vibes.
• Inference economics:
  Optimize AI workflows for speed and cost: model routing, prompt caching, and choosing self‑hosted vs. frontier models based on the quality/cost trade‑off.
• Engineering excellence:
  Testing, design patterns, CI/CD, and observability. Everything ships as production software, and you help set the bar for what good looks like.

• 5+ years building and operating production software at meaningful scale, with end‑to‑end ownership (not just shipping isolated features).
• Strong software design fundamentals: testing, design patterns, clean architecture.
• Backend depth: RESTful APIs, relational databases and SQL, distributed and event‑driven patterns (queues, messaging) behind high‑traffic services.
• Full production ownership: CI/CD, observability, infrastructure. "Done" means healthy in production, not merged.
• Proficient business English.

• 1 to 2+ years shipping LLM applications to production (not just prototypes), with hands‑on command of context engineering, RAG, multi‑agent orchestration, and evals.
• You've personally authored skills, sub‑agents, evals, or verification harnesses, and can walk us through something real you built.
• You think in measurements: baselines, before/after…