Design and build AI agent systems, including agent lifecycle management, orchestration, and execution control.
Develop scalable pipelines for tool invocation, agent planning, memory, and state management.
Collaborate with AI researchers to operationalize research outputs into reliable agent behaviors.
Define and enforce best practices for agent reliability, safety, observability, and cost control.
Lead the design of APIs and services supporting agent runtime and coordination.
Drive architectural decisions for agent frameworks and integrations across AI services.
Troubleshoot complex system-level issues involving agent behavior, performance, or failure modes.
Mentor engineers and provide technical leadership within the AI engineering organization.

Bachelor’s degree in Computer Science, Software Engineering, or a related field
5+ years of experience in backend or distributed systems engineering, with increasing technical ownership
Strong proficiency in Python, with experience designing complex backend services
Experience building production systems involving LLMs, AI services, or agent-like workflows
Deep understanding of RESTful APIs, service-oriented architectures, and system scalability
Experience with cloud platforms (AWS, GCP) and containerized environments (Docker, Kubernetes)
Strong debugging skills across distributed systems, including logs, traces, and metrics
Excellent communication skills and the ability to collaborate across research and engineering teams

AI Engineer, Agent Systems

Key skills