Software Engineer, Agent Harness
AI Tools
Tech Stack
Agent Workflow
Build core agent behavior and capabilities spanning agent orchestration, tools, guardrails, and model behavior tuning. Advance the agent harness including agent loop, tools, prompts, execution environment, and multi-agent coordination capabilities.
About the Role
Software Engineer, Agent Harness
Company: Cursor Department: Engineering Location: San Francisco
Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense.
About the Role
As a Software Engineer on the Agent Harness team at Cursor, you'll build the core agent behavior and capabilities that power agent experiences across Cursor products. This spans agent orchestration, tools, guardrails, and model behavior tuning, designed as a platform that Cursor engineers can extend and depend on. Your work will also define the default Cursor agent experience ("Auto"), where users trust us to make the right model choices under real-world constraints.
Example projects include
- Advancing the agent harness (agent loop, tools, prompts, execution environment, capabilities) used across Cursor products. This would shape and empower experiences like multi-agent coordination.
- Improving the default Cursor agent experience (the "Auto" model setting): making smart model choices based on user needs, model capabilities, and cost appetite.
- Shaping the default Cursor agent's personality.
- Launching new models on Cursor end-to-end, partnering with foundational model providers and the research team on integration, evaluation, and rollout.
You may be a fit if
- You have built complex agentic products or infrastructure.
- You have strong software engineering fundamentals and enjoy shipping production systems.
- You have taste and strong opinions on model and agent behaviors.
- You stay up-to-date and informed on emerging research and industry trends.
- You make good calls in the gray area: weighing data, user experience, and product taste when there isn't a single "right" answer.
- Experience building eval datasets or frameworks to understand and improve the performance of AI systems is a plus.
- Experience building products or tools used by other engineers is a plus.
