Temporal provides a reliable foundation powering AI leaders such as OpenAI, NVIDIA, Cursor, Lovable, Replit, and others. Its adoption is expanding to users spanning a broad range of AI applications ranging from agents to data pipelines and everything in between. The mission of the AI Foundations team is to accelerate Temporal adoption across the entire ecosystem. Our approach combines a deep understanding of use cases with rigorous application of computer systems and software design principles. In this role, you will lead our agent agent optimization efforts. You will design tools and mechanisms to help Temporal users build agents that are optimized for token spend and response time while maintaining result quality. Model routing is a first step, but represents the tip of the iceberg of techniques that we can apply. For example, multi-agent architecture, cache policy, and context management are all relevant. Candidates for this role should have direct experience with this problem domain. You will work closely with other AI Foundations team members, e.g., those who focus on agentic development, maintaining a set of agents skills that lift performance of Codex, Claude Code, and similar tools for developers of Temporal applications. Other team members build ecosystem integrations or develop policy and security systems. If you thrive on blending theory and practice, then this is the right team for you. We are an action-oriented group that loves to ship fast and solve customer problems. We also seek thorough technical grounding for our work and invest in systems and practices that foster long-term success. Most of Temporal’s work is open source—see for yourself here: https://github.com/temporalio [new window]
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Job Type
Full-time
Career Level
Senior
Education Level
Associate degree