4 hours ago
Base Salary
$150k - $250k/yr
Responsibilities
- Build and maintain infrastructure that enables AI agents to complete tasks reliably across many iterations.
- Design memory systems that retain client context from messy operational data over time.
- Develop evaluation harnesses to inform production deployment decisions for LLM systems.
- Measure, test, debug, and improve agent systems, including their ability to learn from failures.
- Ship agent systems and iterate based on production feedback.
- Contribute to infrastructure, orchestration, customer collaboration, and team growth as needed.
Requirements
- At least 3 years of experience building and shipping LLM agents that ran unattended in production for real users.
- Strong Python skills and hands-on experience building production systems.
- Experience implementing memory and context retrieval for real operational data beyond demo RAG projects.
- Experience with agent orchestration, infrastructure, workflow management, retries, and failure recovery.
- Experience building evaluation harnesses for LLM systems that informed production deployment decisions.
- Experience building agent tools, frameworks, or libraries, or leading a technical project from conception to production.
- Open-source contributions to agent tooling or LLM infrastructure are a plus.
Benefits
- Base salary of $150,000 to $250,000 USD annually, with meaningful early equity.
- Visa sponsorship and relocation support are available.
- On-site work in San Francisco, United States.