Forward Deployed Engineer

Box•Redwood City, CA

1d•Hybrid

About The Position

Box is the leader in Intelligent Content Management, enabling organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. This role focuses on closing the gap between AI models and the context needed for them to be useful within a business. The Forward Deployed Engineer (FDE) works with customers to build content-centric AI workflows, acting as a partner to design, build, and deploy solutions that leverage Box at the center of their intelligent content strategy. FDEs turn customer content into the context that makes AI and agents useful.

Requirements

7+ years of development, consulting, professional services, or sales engineering experience.
Expertise in architecture / system design for cloud solutions (APIs, DevOps, Infrastructure, middleware, scale limits, rate limits, etc.).
Expertise in Enterprise Content Management systems and cloud migrations.
Deep understanding of prompt engineering, prompt governance, evaluation and testing frameworks, model selection, benchmarking, and security/compliance scoping for AI.
Proven experience designing and building production AI workflows or agentic systems (not just proof-of-concept).
Hands-on proficiency with AI APIs and at least one major model ecosystem (OpenAI, Anthropic, Google, or equivalent); able to evaluate, confidence score, and select models by capability, cost, and task fit.
Strong programming skills (Python and/or JavaScript) with experience building scripts, API integrations, and automation pipelines that move through a customer SDLC.
Experience in post-sale professional services or consulting environments; comfortable owning customer relationships and driving outcomes over multi-month engagements.
Experience with agentic frameworks and orchestration (LangChain, LlamaIndex, AutoGen, or similar).
Familiarity with retrieval-augmented generation (RAG), context pipeline design, and prompt engineering at production scale.
Understanding of enterprise content governance, information architecture, and data security considerations in AI deployments.
Experience with LLM evaluation methodologies (building evals, confidence scoring, human-in-the-loop review workflows).
Experience working alongside model providers' forward-deployed teams in a complementary, context-layer capacity.
Collaborative partner able and excited to work alongside customers and their preferred partners to deliver best-in-class solutions.

Nice To Haves

You are energized by the pace of AI — you follow model releases, emerging agentic patterns, and evolving best practices because you're genuinely curious, not because it's required.
You think in systems and outcomes, not just features — you care whether AI makes a real difference to a business process, not just whether a model can generate an answer.
You are comfortable translating complex technical concepts for executives and business stakeholders, and equally at home in a code editor or a whiteboard session.
You bring consulting discipline to technical work — you formalize requirements, track deliverables, and hold yourself accountable to measurable customer value.
You thrive in ambiguity and fast-moving environments — Box FDEs are often working at the frontier of what's possible, and the best ones lean into that.
You are a trusted partner to customers, not a just a vendor — you understand their business deeply and advocate for their outcomes inside Box.
You love working in a dynamic environment where ambiguity is common...and can effectively speak to both technical and non-technical parties.

Responsibilities

Prepare enterprise content for AI by assessing and structuring customers' content environments (information architecture, metadata, permissions, governance) so models and agents can retrieve relevant, secure, and current content.
Design relationship hierarchies, metadata libraries with associated templates, Hubs, integrations, and permissions for agentic use cases.
Run AI readiness assessments and deliver actionable roadmaps for customers preparing for Box AI-driven workflows.
Design and build AI workflows and agents by partnering with customer AI leadership to define strategy, set priorities, and deliver roadmaps.
Lead requirements workshops to formalize scope into achievable, tracked deliverables.
Build production-quality code (scripts, apps, API integrations) that scales correctly and handles failures gracefully.
Design and build end-to-end agentic workflows directly in customer environments, including context pipelines, prompts, generative steps, agents, and downstream integrations.
Run programmatic model testing across approved models to find the best fit per use case, building dashboards to track reliability, speed, accuracy, and cost.
Design solutions with AI unit and token efficiency at the center, forecasting spend and supporting ROI calculations.
Own post-deployment reliability, including monitoring, alerting, fallback paths, drift detection, and change control.
Tune workflows as prompts drift, agents multiply, and models change, refining for cost and output quality.
Drive end-user adoption through enablement, roadshows, and LOB-specific configuration.
Document product gaps and work with Box Product & Engineering to influence roadmap priorities.
Track KPI attainment and adoption signals post-launch, packaging learnings into repeatable patterns that scale across customers.
Evolve deployment strategy with customers as AI approaches and models advance.