Staff Engineer

Emergent builds autonomous coding agents that replace traditional software development by generating, testing, and deploying production applications directly from plain-language intent. Our systems run in production at global scale and are used to build millions of real applications.

Since public launch, Emergent has reached $100M ARR in 8 months. 6M+ users across 190+ countries have built 6.5M+ applications on Emergent. We've raised $100M+, backed by Khosla Ventures, SoftBank, Google, Lightspeed, Prosus, Together, and Y Combinator.

We're solving the hard part of AI-driven software creation: correctness, reliability, security, and scale in real production systems. The team is built by repeat founders, Olympiad medalists, and leaders from Google, Amazon, and Dropbox.

We're hiring builders who want ownership, speed, and impact at global scale.

We're not building another developer tool. We're building the system that replaces software development itself. As a Staff Engineer on Autonomous Systems, you will define the technical foundation for how AI agents reliably generate, test, and deploy production-grade software at global scale. This role exists for engineers who think in systems, care about correctness as much as speed, and want to solve problems that don't have playbooks.

• →Architect autonomous systems where AI agents reliably generate production-grade software, with feedback loops for self-correction, validation, and continuous improvement.
• →Build infrastructure that supports millions of applications and real-time workloads, solving for latency, concurrency, and reliability at global scale.
• →Establish standards for correctness, observability, and fault tolerance across backend, infrastructure, and AI layers.
• →Collaborate deeply with AI/ML, infrastructure, and product teams to build end-to-end systems from model interaction layers to distributed execution engines.
• →Debug non-deterministic systems, design for edge cases you can't enumerate, and build systems that reason, not just execute.
• →Mentor engineers and influence technical culture and direction across teams.

• 8+ years of experience building large-scale backend or distributed systems.
• Strong proficiency in Python and/or Go.
• Deep understanding of distributed systems, concurrency and parallelism, and system design under scale and failure.
• Proven track record of owning architecture for critical production systems, not just contributing to them.
• You think in trade-offs, simplify complex systems without dumbing them down, and have influenced engineering direction across teams.
• Experience with AI/ML infrastructure or LLM-based systems is a strong plus.
• Familiarity with Kubernetes, Docker, AWS/GCP/Azure, event-driven systems, and data infrastructure is a bonus.