Software Engineer Iii, Agents Platform

Box Box · Enterprise · Redwood City, CA · Core Platform

Software Engineer III role focused on building the core components of an enterprise-grade Agents Platform, including agent frameworks, tooling, multi-agent workflow orchestration, and integration with LLMs and enterprise systems. The role emphasizes building secure, reliable, and scalable services for agent development and operation.

What you'd actually do

  1. Design, build, and maintain core components of the Agents Platform that power agentic use cases (e.g., Deep Search, Deep Research).
  2. Implement and evolve agent and tool repositories, SDKs, and developer tooling to streamline agent development, testing, and deployment.
  3. Contribute to a multi-tenant control plane that enforces isolation, fair resource allocation, and per-tenant SLAs across agent workloads.
  4. Develop high-throughput, low-latency services with strong observability, guardrails, and secure execution environments.
  5. Collaborate with ML engineers and partner product teams to translate requirements into scalable capabilities on top of LangGraph.

Skills

Required

  • 3+ years of professional software engineering experience building and operating backend or platform services at scale
  • Proficient in an object-oriented language (e.g., Java, C++, C#, Scala) and comfortable with modern service development patterns
  • Solid grasp of distributed systems, data structures and algorithms, API design, and platform architecture fundamentals
  • Experience building and debugging production systems with strong logging, metrics, tracing, and alerting
  • Comfortable owning projects end-to-end: scoping, design, implementation, testing, rollout, and iteration
  • Strong collaborator with clear communication skills; able to work cross-functionally with ML, product, and security partners

Nice to have

  • Experience with agent frameworks or orchestration tools (e.g., LangGraph, LangChain) or workflow engines
  • Familiarity with LLM concepts (RAG, semantic search, indexing, ranking/relevance) and integrating with cloud ML platforms (Vertex AI, AWS Bedrock, SageMaker)
  • Exposure to Kubernetes-based systems, service meshes, or containerized workloads
  • Experience building SDKs, developer platforms, or internal tooling that accelerates engineering teams
  • BS in Computer Science or related field (or equivalent practical experience)

What the JD emphasized

  • enterprise AI
  • AI agents
  • agentic use cases
  • agent development
  • multi-agent workflows
  • enterprise systems
  • secure execution environments
  • LangGraph

Other signals

  • building an enterprise-grade Agents Platform
  • design, deploy, and operate AI agents
  • orchestrate multi-agent workflows
  • integrate with multiple LLMs and enterprise systems