Why Work at Lenovo

We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 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).

• Leadership & Management: Manage and mentor DevOps and Engineering teams responsible for continuous integration/deployment pipelines, cloud infrastructure, uptime SLAs, and automation of security tools. Provide strategic direction and support to engineering managers, project managers, and scrum masters, fostering a culture of innovation and collaboration.
• Technical Strategy: Set the long-term technical direction and strategy for cloud infrastructure and platform, contributing to broader engineering processes. Champion reliability, performance, and scalability of core infrastructure services (AWS, Azure), focusing on metrics-driven decision-making and data analysis.
• Budget & Resource Planning: Own the cloud and infrastructure budgets, resource planning, and operational expense execution. Develop financial models in collaboration with Engineering Leadership and Finance Ops teams, ensuring alignment with organizational objectives.
• Stakeholder Collaboration: Collaborate with business and engineering stakeholders to define and support the Cloud Infrastructure roadmap. Co-develop infrastructure standards, documentation, and processes, establishing infrastructure-wide SLOs, KPIs, and metrics.
• Security & Reliability: Infuse site reliability and security into all aspects of Lenovo's cloud infrastructure, ensuring stability, reliability, and high performance. Implement modern software security practices and secure software systems within cloud-based infrastructure.
• Team Empowerment & Development: Empower teams to continuously improve processes and culture, fostering the happiness and development of engineers. Mentor Engineering Managers and individual contributors, driving professional growth and excellence.
• Commitment & Support: Ensure teams consistently deliver value by actively removing roadblocks and supporting dependent teams. Maintain a focus on meeting commitments and driving results aligned with organizational goals.

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience.
• 12+ years of experience in a software engineering environment, including 6+ years in engineering management roles.
• Prior experience supporting AI solutions and utilizing AI tools to enhance engineering efficiencies.
• Demonstrated leadership in managing global DevOps teams and offshore squads.
• Strong technical background in infrastructure platform container frameworks (e.g., Kubernetes), production database engines, and metrics tooling.
• Experience with cloud platforms (e.g., AWS, Azure) and CI/CD pipeline tooling (e.g., Jenkins, GitLab).

• 15+ years of experience in a software engineering environment, with 10+ years in engineering management roles.
• Extensive experience in DevOps or Cloud Engineering management, including managing large teams and overseeing significant initiatives.
• Proven experience as a DevOps Engineer or SRE, with a strong software development and automation background.
• Expertise in deployment and management of LLMs, including technologies like RAG.
• Proficient in CI/CD tools (Jenkins, GitLab CI, CircleCI) and infrastructure as code (Terraform, Ansible)
• Solid knowledge of container orchestration technologies (Kubernetes, Docker)
• Familiarity with MLOps tools and practices to support machine learning lifecycle management
• Experience with cloud services (AWS, GCP, Azure), particularly in AI/ML deployments
• Background in monitoring tools like Prometheus, Grafana, and ELK stack
• Understanding of Python, particularly in data science and machine learning contexts
• Proven track record of executing customer-facing infrastructure initiatives across diverse product teams.
• Excellent leadership, influencing, and communication skills, focusing on driving continuous performance improvements.
• Proficiency in managing Azure, AWS, or distributed VMware environments, along with expertise in container technologies and code management tooling.