位于北京市, c22的 20 个优质staff engineer, digital design engineering职位（正在招聘！）

Lenovo is a US$83 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.

Description and Requirements

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.

Additional Locations:

China - Beijing - 北京（Beijing）

China

China - Beijing

China - Beijing - 北京（Beijing）

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在北京市, c22的staff engineer, digital design engineering个职位

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