Software Engineer III, Core Agents

Box•Redwood City, CA

1d•Onsite

About The Position

Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. WHY BOX NEEDS YOU AI is transforming how enterprises work, and Box is building an enterprise-grade Agents Platform at the core of the Box Content Cloud. Our platform, built on LangGraph, enables teams across Box and our customers to design, deploy, and operate AI agents that handle real-world enterprise workflows—from content understanding and generation to intelligent metadata, automation, and complex, multi-step orchestrations. As a founding Software Engineer on the AI Agents team, you will build the core platform that makes agent development secure, reliable, and scalable. You’ll own systems that define agent frameworks and tooling, orchestrate multi-agent workflows, integrate with multiple LLMs and enterprise systems, and enforce tenant isolation, data governance, and least-privilege access. You’ll deliver low-latency, high-throughput execution with robust observability, guardrails, and safe execution environments, ensuring agents perform predictably in production. Your work will empower product teams at Box and enterprise customers to build, customize, and operate agents for critical use cases—answering complex questions, automating content-centric processes, and coordinating actions across business systems. You’ll help establish patterns, SDKs, and best practices on top of LangGraph so developers can ship agents quickly and safely, all on a platform engineered for reliability and scale.

Requirements

Familiarity with at least one object oriented language like C, C++, Java, Scala
BS degree in Computer Science or a related
Strong understanding of distributed systems, data structures & algorithms, platform architecture.
3+ years of industry experience in computer science, machine learning or related field
You are passionate about building infrastructure that powers AI systems
You like to be an owner and strive to do work you're proud of, both technically and in your team interactions
Able to inspire other people to work with you, and you enjoy mentoring and coaching, as well as learning from other engineers
You've built, deployed, and supported distributed systems at scale
You have strong analytical and problem-solving skills, with the ability to work with large and complex systems

Nice To Haves

Advanced degree in computer science or related field.
Familiarity with concepts related to Large Language Models, Retrieval Augmented Generation (RAG) , Semantic Search, Indexing, Ranking and Relevance
Familiarity with cloud based ML platforms such as Vertex AI, AWS Bedrock, AWS Sagemaker etc
Experience with LangChain/LangGraph or other agent definition languages
Experience with Kubernetes bases systems

Responsibilities

Build core components of the Agents Platform that power agentic use cases like Deep Search and Deep Research.
Design and implement agent and tool repositories, along with observability and CI/CD pipelines, to streamline agent development and deployment.
Develop and evolve a multi-tenant control plane that enforces isolation, fair resource allocation, and per-tenant SLAs across all agent workloads.
Collaborate with ML engineers to translate requirements into scalable capabilities on top of LangGraph.
Contribute to technical discussions and provide guidance on cross-team projects within the AI Platform organization.

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