康明斯(中国)投资有限公司东亚共享服务中心
AI Lab Infrastructure and Operations Manager
Skills
9 days ago
Share this opportunity
Share this opportunity to other talents of your network:
✓ Offer them a visibility boost with clients.
✓ Help your contacts find their next job.
Important information
Contract type:
Permanent
Salary:
CN¥480,000 – CN¥600,000 / year
Location:
Beijing, China
Work mode:
Onsite
Published on:
16 October 2026
What they need
About 该职位来源于猎聘 About Cummins AI Lab The Cummins AI Lab integrates applied AI research, engineering workflows, manufacturing processes, and enterprise platforms to deliver high-value AI solutions across Cummins' global operations. We build and operate the infrastructure, technology ecosystem, and experimentation environment that enable rapid AI innovation, proof-of-concept validation, and scalable enterprise AI adoption. Role Overview The AI Lab Infrastructure & Operations Manager is responsible for the secure, reliable, and efficient operation of the AI Lab environment. This role leads the management of:
- AI platforms and cloud services
- GPU and computing resources
- Hardware and laboratory infrastructure
- Vendors and contractors
- Operational governance and service delivery
- Infrastructure and operations teams The role focuses on platform operations, resource management, governance, compliance, service continuity, and operational excellence rather than AI algorithm development or platform architecture design. Key Responsibilities AI Platform & Service Operations
- Manage AI cloud environments, AI platforms, hosted AI services, model APIs, and subscriptions.
- Lead onboarding, configuration, maintenance, and lifecycle management of AI services.
- Evaluate and introduce foundation models, inference services, deployment frameworks, and AI tools.
- Assess usability, compatibility, reliability, security, scalability, and cost.
- Maintain service inventories, ownership records, access management, and support processes.
- Coordinate incident management, service changes, renewals, and vendor escalations. Infrastructure & Computing Resource Management
- Manage AI servers, GPU clusters, AI workstations, and lab infrastructure assets.
- Plan resource allocation, workload scheduling, capacity management, and computing availability.
- Monitor utilization, operational risks, maintenance status, and service performance.
- Lead asset lifecycle management including inventory, upgrades, warranty tracking, and maintenance.
- Coordinate infrastructure deployment and support with vendors and enterprise IT teams. Environment Operations & Governance
- Lead day-to-day operations of the AI Lab environment.
- Manage networks, identities, access controls, storage, and supporting services.
- Establish standards for access management, asset governance, change management, incident management, and operational processes.
- Maintain operational documentation, runbooks, dashboards, and service records.
- Drive operational excellence, business continuity, risk prevention, and process improvement. Security, Compliance & Risk Management
- Ensure compliance with cybersecurity, privacy, data protection, and governance requirements.
- Partner with IT, cybersecurity, procurement, legal, and enterprise governance teams.
- Support access control, data classification, vulnerability management, secure configuration, logging, patching, and remediation.
- Evaluate operational and security impacts of introducing new AI technologies and external services.
- Track risks, exceptions, incidents, and corrective actions. Technology Evaluation & Innovation Enablement
- Assess emerging AI platforms, infrastructure technologies, hardware solutions, and productivity tools.
- Coordinate technical evaluations with researchers, architects, users, vendors, and contractors.
- Recommend technology adoption, resource planning, and future infrastructure investments.
- Support PoC teams by provisioning environments and computing resources.
- Capture and share evaluation findings and best practices. Vendor, Contractor & Budget Management
- Manage relationships with cloud providers, hardware vendors, software suppliers, and service partners.
- Define work packages, monitor deliverables, and manage contractor performance.
- Support procurement activities including contracts, licensing, renewals, warranties, and service agreements.
- Monitor infrastructure spending, utilization, budget risks, and optimization opportunities.
- Lead issue resolution across vendors, contractors, IT teams, and AI Lab stakeholders. Team Leadership
- Lead infrastructure and operations personnel, contractors, and support teams.
- Set priorities, assign work, track performance, and build a service-oriented culture.
- Develop team capabilities in platform operations, governance, documentation, and support.
- Define and monitor service KPIs such as availability, utilization, incident response, and customer support.
- Develop and execute the AI Lab infrastructure and operations roadmap. Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, AI, or related disciplines.
- Experience in infrastructure operations, platform operations, IT service management, technical operations, or laboratory operations.
- Hands-on experience managing cloud platforms, enterprise technology services, servers, networks, or technical environments.
- Experience managing vendors, contractors, and technical service providers.
- Demonstrated people leadership and stakeholder management experience.
- Knowledge of cybersecurity, access control, data protection, asset management, incident management, and operational risk management.
- Strong project management, communication, documentation, problem-solving, and cross-functional collaboration skills.
- Ability to manage multiple priorities in a fast-paced innovation environment. Preferred Qualifications
- Experience supporting AI, data science, software engineering, innovation labs, or research environments.
- Familiarity with generative AI platforms, foundation models, model APIs, deployment approaches, and inference frameworks.
- Experience managing GPU servers, AI appliances, HPC resources, or shared computing platforms.
- Experience with cloud cost management, software licensing, procurement, vendor management, and SLA governance.
- Experience within engineering, manufacturing, industrial, or enterprise technology organizations.
- Understanding of the AI solution lifecycle from experimentation through production deployment. What You Will Gain
- Ownership of the operational foundation that enables enterprise AI innovation.
- Exposure to cutting-edge AI platforms, infrastructure, models, and emerging technologies.
- Leadership opportunities across AI teams, enterprise IT, cybersecurity, procurement, vendors, and business stakeholders.
- The opportunity to build and scale operational practices for a world-class enterprise AI Lab. * Cummins is an equal employment opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons, without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, and/or expression, or other status protected by law. If you require any reasonable adjustments to accommodate a health condition or disability, please let us know. Your journey with us matters. *康明斯是一家提供平等就业机会的雇主。我们致力于为所有符合条件的候选人提供平等的就业机会,不因种族、性别、肤色、残障、国籍、年龄、宗教信仰、工会身份、性取向、退伍军人身份、公民身份、性别认同及/或性别表达,或其他受法律保护的身份而区别对待。如您因健康状况或残障需要合理便利,请随时告知。您在康明斯的职业旅程对我们至关重要。
Other offers great for you!
These companies are also looking for great profiles
Visian
Senior AI Engineer / Data Scientist Senior – Intelligence Artificielle
650
Freelance
Paris, France
Hybrid
Skills
6 days ago
Quick apply
Espace Freelance
Audit Applicatif support & Intelligence artificielle
Freelance
Lille, France
Onsite, Hybrid
Skills
6 days ago
Quick apply
Yunik
PMO Senior – Data Science & Intelligence Artificielle (H/F)
Freelance
Paris, France
Hybrid
Skills
1 day ago
Quick apply