Founding Engineer, Agentic Systems

• Build a context and self-learning system that uses accumulated knowledge to improve agent performance.
• Develop self-healing workflows that detect production failures, diagnose their causes, and recover autonomously.
• Build and maintain the agent harness and meta-harness for creating, evaluating, and evolving agents quickly.
• Set patterns for agent context, tracing, evaluation, and iterative improvement across the product.
• Work closely with the technical leadership team, experiment rapidly, and help hire and grow the agent engineering team.
• Two to nine years of professional software engineering experience and a completed or in-progress engineering, computer science, or quantitative degree from a strong technical university.
• Recent experience building agentic software, with a harness-centric approach to context engineering and evaluation-driven iteration.
• Experience building context or self-learning systems, agent tracing and evaluations, and autonomous failure detection, diagnosis, or recovery workflows.
• A record of shipping working software into production, not research alone, and experience building reusable agent harnesses is valuable.
• Strong early-stage startup experience as a funded founder or engineer at a venture-backed pre-seed, seed, or Series A company.
• Relevant technologies include TypeScript, Effect-TS, PostgreSQL, and large language model agent systems.
• On-site in San Francisco, California. Candidates based elsewhere in the United States may be considered with a concrete relocation plan to San Francisco.

None flagged.