位于c22的 20 个优质development executive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

Solution Architecture & Pre-Sales

Lead end-to-end solution architecture and pre-sales for Cloud Management, AIOps, FinOps, and AI platform solutions.
Conduct customer discovery to assess cloud operations, monitoring maturity, AI readiness, and business challenges.
Translate requirements into scalable architectures, solution blueprints, proposals, demos, and executive presentations.
Articulate measurable business value, including SLA improvement, MTTR reduction, productivity gains, infrastructure efficiency, and cost optimization.

Cloud Management & AI-Native Operations

Design integrated platforms covering observability, event correlation, anomaly detection, root cause analysis, automation, ITSM, and CMDB.
Architect closed-loop operations from monitoring and AI analysis through automated remediation and continuous optimization.
Enable L2/L3 autonomous operations using AI agents, multi-agent workflows, and human-in-the-loop controls.
Support private, hybrid, and multi-cloud environments with consistent governance and operational standards.

AI Platform & Model Operations

Design enterprise AI platforms supporting model onboarding, deployment, serving, monitoring, evaluation, versioning, and governance.
Develop MLOps and LLMOps architectures for traditional AI models, foundation models, generative AI applications, and AI agents.
Define model observability across quality, drift, hallucination, latency, throughput, token usage, inference cost, and GPU utilization.
Design AI gateways, model routing, inference optimization, and scalable model-serving architectures.
Integrate AI platforms with cloud infrastructure, data platforms, observability tools, ITSM, and enterprise workflows.

FinOps & AI Cost Optimization

Design FinOps frameworks for cost visibility, allocation, forecasting, budget governance, and continuous optimization.
Optimize cloud and AI workload costs through rightsizing, workload placement, GPU utilization, token management, and inference efficiency.
Balance model quality, performance, availability, and cost.

Automation & Integration

Design orchestration, runbooks, event-driven workflows, and AI-driven automation.
Integrate monitoring, ITSM, CMDB, cloud, Kubernetes, infrastructure, AI, data, and security platforms.
Ensure reliable data flows, reusable integration patterns, governance controls, and operational scalability.

Cross-Functional Collaboration

Partner with product, engineering, sales, and delivery teams to shape product roadmaps and customer solutions.
Support opportunities from discovery and solution design through proposal, proof of concept, deployment, and value realization.
Build reusable solution assets, reference architectures, demos, and best practices.

Job Requirements

8+ years of experience in Cloud Operations, AIOps, SRE, IT Operations Transformation, AI Platforms, or solution architecture.
Strong customer-facing pre-sales, consulting, and solution design experience.
Strong knowledge of observability, event management, ITSM, CMDB, automation, and hybrid or multi-cloud architectures.
Experience with AIOps, intelligent automation, or autonomous operations solutions.
Understanding of AI platforms, MLOps, LLMOps, model serving, model monitoring, AI agents, and generative AI.
Familiarity with GPU infrastructure, Kubernetes, inference platforms, and AI workload optimization.
Knowledge of FinOps, cloud cost management, and AI cost optimization.
Ability to connect technical solutions to measurable business outcomes.
Strong communication, presentation, and executive stakeholder management skills.

Additional Locations:

China - Beijing - 北京（Beijing）

China

China - Beijing

China - Beijing - 北京（Beijing）

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