About the role
TL;DR : We're looking for exceptional builders who help us design and ship the foundational infrastructure that lets Conduct scale to the world's largest enterprises, while accelerating the product teams building on top of it. Why Conduct The world's largest companies are slowed down by the software they run on. We’re building the AI operating system that absorbs IT complexity and unlocks entirely new levels of speed, output, and ambition. We believe this is a generation-defining mission. Major enterprises already trust us with their most critical systems, we just closed a $60M Series A from top-tier funds, and we're still early enough that what you build here defines the company. We're a small, talent-dense team doing our life's work at Conduct - we value extreme ownership, high velocity, and low-ego collaboration. If you bring that same drive, we will make sure this is the place you do yours too. Who we hire We're looking for pragmatic, high-agency engineers who thrive in ambiguity and care as much about the system as the feature. Fundamentals matter more to us than familiarity with any specific tool. If you're strong, you'll pick it up fast. You'll stand out if you: Have 3+ years of backend experience with exposure to platform or infrastructure work. You have seen what it actually takes to go from MVP to scalable, production-grade systems Have strong system design instincts and own problems end-to-end across APIs, infrastructure, and data flows Are experienced with distributed systems, scaling databases (postgres), queueing, and large-scale batch processing Understand how to benchmark and tune systems under real load, and know how to make pragmatic trade-offs when the data is ambiguous Are familiar with LLM infrastructure at scale Raise the bar around you — through code, mentorship, and better systems — and fix problems without waiting for permission What you’ll own You'll have broad ownership across architecture, developer experience and production systems. The infrastructure problems are real and genuinely hard: we process tens of millions of lines of code per customer, generating large-scale LLM workloads under enterprise-grade reliability