Forward Deployed Engineer - Campus Recruitment

Beijing-based enterprise AI company building foundation-model, agentic-AI, and AI-transformation products, including the TrueNorth enterprise decision hub.

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Beijing, China

Funding history

About 01.AI

01.AI develops full-stack enterprise AI solutions, industry-agent applications, and sovereign/industry model-training capabilities.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will work directly with enterprise customers to understand business processes and pain points, turning them into verifiable technical problems. You will quickly build prototypes, demos and POCs using LLM, Agent, RAG and Workflow, handle architecture, development, data processing, system integration and deployment, optimize accuracy, reliability, latency and cost, collaborate across teams, and turn project experience into reusable assets.

Requirements

  • Class of 2027 graduate with bachelor's degree or above; computer, software engineering, AI majors preferred
  • Proficiency in at least one of Python, Java, Go, JavaScript/TypeScript; knowledge of data structures, algorithms, databases and APIs
  • Familiar with LLM principles and AI tools; project experience with AI Agent, RAG, Tool Calling, Workflow
  • Strong problem solving and business understanding
  • Self-driven with ownership
  • Good communication and collaboration
  • Good English communication for technical discussions and customer meetings
  • Interest in enterprise AI deployment; willing to work onsite at customers or travel

Responsibilities

  • Communicate with customers to understand business processes, metrics and pain points and translate them into technical problems and AI scenarios
  • Rapidly build prototypes, demos and POCs using LLM, Agent, RAG and Workflow
  • Take part in architecture design, development, data processing, enterprise system integration, deployment and debugging
  • Build evaluation methods and continuously improve accuracy, reliability, latency, cost and business metrics
  • Collaborate with customer teams and internal engineering, product, solutions and business teams
  • Turn components, tools, evaluation methods and experience into reusable assets