Level AI

Level AI

Senior Backend Engineer- AI Agents (Remote)

United States · Senior

Sponsorship not specifiedDetected 40 days ago
Distributed SystemsCloud PlatformsRESTgRPCMachine LearningLLMsAgentic AIAI OrchestrationCollaborationMentoring

About the role

  • These systems operate in real-time, high-volume enterprise environments and are central to delivering intelligent, production-grade AI experiences.
  • You will work at the intersection of distributed systems, cloud infrastructure, and AI-powered applications-bringing agentic AI capabilities into production at scale.
  • What you'll get to do at Level AI (and more as we grow together):

Responsibilities

  • Design and build scalable backend systems powering AI Agents that operate in real-time enterprise environments
  • Build systems for agent memory, context management, and state persistence across interactions
  • Design and manage event-driven, asynchronous workflows for complex agent tasks
  • Build and maintain robust APIs and service layers (REST / gRPC) for agent capabilities
  • Collaborate with Product and Solutions teams to translate real customer workflows into agentic systems
  • Drive best practices in observability, monitoring, safety, and guardrails for AI systems
  • Opportunity to build cutting-edge AI products at scale

Requirements

  • We'll love to explore more about you if you have:

Skills

  • About Level AI Level AI is on a mission to turn every customer interaction into a strategic advantage.
  • Headquartered in Mountain View, California, Level AI is a Series C company backed by leading investors including Battery Ventures and ENIAC.
  • Architect low-latency inference pipelines integrating LLMs, SLMs, and external tools/services

Compensation

  • Competitive compensation with performance-based upside

Benefits

  • Flexible vacation policy
  • Health insurance coverage
  • Perks & Benefits

Company info

  • https://www.linkedin.com/company/level-ai/

This listing is sourced directly from Level AI's careers page and normalized into a canonical job model.