adaption 路 San Francisco
Agent systems engineer building planning, tool use, memory and recovery for multi-step agents that run against real tools and services under real constraints. Work includes long-running task reliability, self-improving loops, and evaluation and tracing systems with reproducibility. Requires 5+ years building production ML or backend systems and familiarity with the OpenAI Responses API and MCP.
You'll build the agent systems at the core of our product. These systems turn customer goals into reliable, multi-step execution across real tools and services.
This is not about building demos. You'll work on agents that operate under real constraints: incomplete information, external failures, limited budgets, and unpredictable traffic. You'll own how they plan, use tools, recover from errors, and improve over time.
Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to be perfect, but you do need to be adaptable. We encourage you to apply, even if you don't check every box.
Most AI is frozen in place - it doesn't adapt to the world. We think that's backwards. Our mandate is to build efficient intelligence that evolves in real-time. Our vision is AI systems that are flexible, personalized, and accessible to everyone. We believe efficiency is what makes this possible - it's how we expand access and ensure innovation benefits the many, not the few. We believe in talent density: bringing together the best and most driven individuals to push the boundaries of continual adaptation. We're looking for builders and creative thinkers ready to shape the next era of intelligence.