Member of Technical Staff (Software Engineer, Capabilities)

## Responsibilities - Build a deep, hands-on understanding of how frontier LLMs reason and where they break, then turn that into better engine and primitive design. - Bring each new model capability into the product as it reaches the frontier, including planning, long-running tasks, autonomous execution, and self-evolving skills and agents. - Work closely with the agent engine layer (context management, tool calling, planning, long-horizon execution) to turn frontier capabilities into reliable primitives. - Design, build, and own the primitives at the heart of Computer (Skills, Workflows, and Artifacts) so they compose into one coherent experience. - Build the evaluation systems (benchmarks, evals, rubrics, feedback loops) that make each capability best-in-class before broad rollout. - Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and example. ## Requirements - 8+ years of professional software engineering experience, shipping and owning complex systems end-to-end. - Strong backend / Full Stack engineering skills, with experience in designing and building scalable and reliable distributed systems, serving high traffic and a large user base. - Demonstrated technical leadership: you scope ambiguous problems, set direction, and drive cross-team projects to durable outcomes. - Strong product judgment and ownership instincts; you turn vague needs into simple, reliable systems and ship without waiting for perfect specs. - Comfort with data-informed decisions; you define the metrics and evals that prove a system works, and iterate on them. - Genuine interest in AI products, with hands-on adoption and a willingness to learn quickly. ## Nice to Have - Experience building agentic systems (tool calling, subagents, long-running or autonomous task execution). - Experience building developer platforms or reusable-capability primitives (SDKs, plugin systems, workflow engines). - Experience with evaluation, benchmarking, or quality systems for ML/LLM-powered products. - Time spent at a fast-growing startup or on a high-ownership engineering team. ## Benefits - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence.