Forward Deployed Engineer

Box Box · Enterprise · Redwood City, CA · Box Consulting

Forward Deployed Engineer at Box, focused on building and deploying AI-driven content management workflows and agentic systems for enterprise customers. This role involves preparing content for AI, designing and building AI workflows and agents, and optimizing deployed solutions, acting as a technical partner to customers.

What you'd actually do

  1. Assess and structure customers' content environments — information architecture, metadata, permissions, and governance — so models and agents can retrieve the most relevant, secure, and current content
  2. Design and build end-to-end agentic workflows directly in our customer’s environments: context pipelines, prompts, generative steps, agents, and downstream integrations, including Box MCP server and customer-chosen orchestrators
  3. Lead requirements workshops to formalize scope into achievable, tracked deliverables
  4. Build production-quality code — scripts, apps, API integrations — that scales correctly and handles failures gracefully
  5. Own post-deployment reliability: monitoring, alerting, fallback paths, drift detection, and change-control so solutions stay accurate and trusted over time

Skills

Required

  • Experience in development, consulting, professional services, or sales engineering
  • Ability to build AI workflows and agents
  • Experience with production-quality code and API integrations
  • Understanding of content management systems and information architecture
  • Customer-facing communication and partnership skills
  • System design and outcome-oriented thinking

Nice to have

  • Experience with Box AI
  • Familiarity with various AI models and orchestrators
  • Knowledge of AI readiness assessments and roadmapping
  • Expertise in monitoring, alerting, and drift detection for AI systems

What the JD emphasized

  • customer AI leadership
  • production-quality code
  • end-to-end agentic workflows
  • AI unit and token efficiency
  • post-deployment reliability
  • tune workflows
  • Document product gaps
  • evolve deployment strategy

Other signals

  • customer-facing AI solutions
  • building AI workflows and agents
  • production-quality code for AI systems
  • optimizing AI solutions post-deployment