基本信息

职位编号:
WD00101133
工作领域:
Information Technology
国家/地区:
中国
省:
北京
市:
北京(Beijing)
日期:
星期一, 6 月 22, 2026
工作性质:
Full-time
其他工作城市
* China - Beijing - 北京(Beijing)

为什么选择联想

联想文化,我们称之为 “We Are Lenovo”(我们,就是联想),其核心是:“说到做到,尽心尽力,成就客户”。

联想集团是一家年收入830亿美元的全球化科技巨头,位列《财富》世界500强第196名,服务遍布全球180个市场数以百万计的客户。为实现“智能,为每一个可能” 的公司愿景,联想在不断夯实全球个人电脑市场冠军地位的基础上,积极构建全栈式的计算能力,现已拥有包括人工智能赋能、人工智能导向和人工智能优化的终端、基础设施、软件、解决方案和服务在内的完整产品路线图,包括个人电脑、工作站、智能手机、平板电脑等终端产品,服务器、存储、边缘计算、高性能计算以及软件定义等基础设施产品。这一变革与联想改变世界的创新一起,共同为世界各地的人们成就一个更加包容、值得信赖的智慧未来。联想集团有限公司在香港交易所上市(港交所:992)(美国预托证券代号:LNVGY)。

欢迎访问联想官方网站 https://www.lenovo.com,并关注“联想集团”微博及微信公众号等社交媒体官方账号,或关注“联想招聘”公众号,获取联想最新动态。

职位描述和要求:

Job Responsibilities:

Deep Business Relationship Management & Expectation Setting 

  • Strategic Alignment & Proactive Enablement: Regularly participate in business unit operating reviews to deeply understand annual KPIs and pain points. Proactively propose IT and AI solutions that address these challenges. Shift from “passive order‑taking” to “active value‑delivery,” positioning yourself as a business partner rather than a back‑office supporter.
  • AI Use‑Case Discovery & Value Articulation: Actively engage with each business function to identify and prioritise high‑impact AI/GenAI applications (e.g., intelligent Q&A, contract comparison, demand forecasting, RPA‑based auto‑entry). Translate AI’s ROI into business to eliminate the perception.
  • Stakeholder Mapping & Influence: Identify key decision‑makers, influencers, and potential blockers within each business unit. Tailor your communication strategy accordingly. Maintain executive trust through regular one‑on‑one lunches or quarterly business reviews (QBRs), ensuring that business heads come to you first with system or AI concerns, rather than escalating complaints to senior management.

Internal Negotiation & Conflict Resolution 

  • Priority Bargaining (Resource Allocation): Facing multiple business units submit urgent IT or AI demands simultaneously – and IT resources (development, operations, compute, budget) are limited – lead an internal negotiation. Use data and objective criteria (urgency, business impact, expected value) to guide stakeholders toward a consensus on sequencing, persuading lower‑priority requesters to defer or scale back, ensuring resources are concentrated on the company’s highest‑value strategic initiatives.
  • Scope Definition & Anti‑Scope‑Creep: Faced with vague or ever‑changing requirements, employ professional negotiation techniques to define a Minimum Viable Product (MVP) boundary. Strike the right balance between “everything we want” and “technical feasibility/cost.”
  • AI Expectation Management (Critical Addition): Counter overly optimistic expectations about AI (especially LLMs by presenting quantitative metrics . Use live demos, industry benchmarks, and data samples to “cool down” expectations, clearly defining the capability boundaries, accuracy ceilings, and the need for human‑in‑the‑loop fallback mechanisms, thus avoiding trust erosion due to unmet expectations.
  • Data Readiness & Governance Cost Bargaining: Convince business owners to invest the necessary human resources for data cleansing, labelling, and structural remediation, articulating clearly that “high‑quality data in = high‑value AI out.”

Change Management & Crisis Communication

  • Pre‑launch Expectation Guidance: Before new systems or AI features go live, proactively communicate the “pain period” to business heads, managing their desire for perfectionism and persuading them to embrace an iterative, phased rollout.
  • Major Incident Negotiation & Buffering: In the event of a critical system failure or severe AI “hallucination” that disrupts business operations, act as the primary interface to business executives. Use transparent yet strategic communication to defuse anxiety and anger, buy precious time for the technical recovery team, and minimize negative publicity.

Job Requirements:

Experience & Background

  • Major in Computer Science, Artificial Intelligence, Software Engineering, Information Management, or a related field (Master’s preferred).
  • 8+ years of experience in enterprise IT / digital transformation, with at least 3+ years in an IT Business Partner (or equivalent stakeholder‑facing technology management) role.
  • Proven track record of delivering 3+ AI/LLM projects from PoC (Proof of Concept) to production.
  • Hands‑on experience with AI enablement in at least one core business domain (Sales, Supply Chain, Finance, Customer Service, etc.).

AI Technical Architecture Skill 

  • Model Selection & Evaluation Framework
  • RAG (Retrieval‑Augmented Generation) Implementation Supervision
  • AI Agent & Tool‑Calling Design
  • Security, Compliance & Content Guardrails
  • Cost Modelling & Performance Optimization

Core Soft Skills (Negotiation & Relationship)

  • Exceptional upward and cross‑functional influencing skills – ability to drive alignment without formal authority, using data, trade‑offs, and empathy.
  • Master of conflict resolution – remains calm and rational in high‑pressure, emotionally charged situations; skilfully turns confrontation into constructive dialogue using “follow‑and‑lead” techniques.

其他工作城市
* China - Beijing - 北京(Beijing)
* China - Beijing - 北京(Beijing)
* China - Beijing
* China