AI Agent Architect

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 our public launch, we've crossed $100M in ARR and grown to over 10M users across 190+ countries. We're 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, IIT & IIM alumni, and leaders from Google, Amazon, and Dropbox.

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

• →Develop deep, evidence-grounded intuition for how the agent thinks, succeeds, and fails across the full range of real-world use
• →Mine production behavior for the failure modes, regressions, and bottlenecks most teams never see, and turn them into clear, quantitative signal
• →Define and run high-leverage experiments that improve agent quality, reliability, and code outcomes, spanning prompt tuning, eval dataset creation, experimentation, and harness engineering
• →Build and evolve evaluation frameworks that measure agent quality at scale: define the metric, build the dataset, validate it against known signals, and ship dashboards that make regressions impossible to miss
• →Ship with rigor through clear metrics, evaluation gates, staged rollouts, and explicit rollback criteria
• →Drive the hard problems in context engineering, memory systems, tool use, and long-horizon execution, where agent reliability is actually won or lost
• →Make hard calls in subjective, probabilistic systems: when a regression is real, when a win is noise, when a benchmark is overfit, when to ship on mixed signals, and when to kill a promising direction
• →Think like the agent and continuously make it smarter, more reliable, and more useful

• 5+ years building and shipping software, with real end-to-end ownership
• At least 1 year of hands-on experience with agentic systems and their evaluation
• Strong systems thinking paired with sharp product judgment
• Hands-on with experimentation, metrics, and debugging, fluent in Python, SQL, or similar for analysis
• Comfortable reasoning about noise, confounds, distribution shift, and selection effects, you know when to trust a number and when to suspect it
• Energized by the long tail, sifting through large volumes of agent behavior to find the rare, hidden failure mode is the fun part for you
• Deep, current interest in LLMs, agents, and emerging model capabilities, you know what shipped last week and why it matters
• An independent operator with leadership presence, you scope your own work and push back on weak ideas, including your manager's
• Bias toward velocity without compromising honest measurement, you know which corners are safe to cut and which are load-bearing

• Principal or Staff ICs, software architects, and lead builders
• Engineers who moved into product and never stopped building
• Technical cofounders who have owned systems end-to-end and want to stay close to the work