Senior Field AI Solutions Engineer

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

Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 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.

• Please Note: This is a fully remote role; however, international travel is expected to collaborate with global RD labs, business units, and pilot customers.***

About Lenovo CTO Org Lenovo CTO Org is the cutting-edge RD and technology incubation organization of Lenovo, dedicated to advancing information technology, smart devices, and services. Our mission is to transform breakthrough innovations into scalable businesses, powering Lenovo’s most advanced products and shaping the future of AI, edge computing, intelligent devices, and enterprise solutions.

About The Role This is a hands-on technical role within the AI Solution Delivery organization of Lenovo CTO Org’s Tech Incubation team, reporting to the Director, AI Solution Delivery.

You will be responsible for deploying and operationalizing AI-powered solutions in real customer environments. Working closely with Product Management, Solution Architects, RD teams, and customers, you will bridge the gap between prototype and production by implementing, integrating, tuning, and validating solutions on-site.

Success in this role requires a combination of software engineering, applied AI, systems integration, and customer-facing problem-solving. You must be comfortable working directly with customers, troubleshooting complex technical issues, and adapting solutions to real-world operating conditions.

This role requires extensive travel and extended customer-site engagements, which may reach 70–80% depending on project needs and incubation phase.

Key Responsibilities AI Solution Deployment Integration

• Deploy AI-powered solutions in customer environments, including edge computing platforms, software applications, sensors, and supporting infrastructure.
• Integrate solutions with customer IT and operational systems, APIs, databases, and enterprise platforms.
• Develop and maintain integration code, automation scripts, and deployment tooling using Python and related technologies.
• Assess customer environments and ensure deployment readiness, connectivity, and system compatibility.

Applied AI Solution Optimization

• Configure, tune, validate, and troubleshoot Computer Vision and AI models in production environments.
• Analyze field performance, identify root causes of accuracy issues, and optimize solution performance for real-world operating conditions.
• Collect and analyze deployment data to support continuous improvement and model refinement.
• Partner with RD teams to communicate field findings and accelerate product maturity.

Customer Delivery Technical Leadership

• Serve as the primary technical lead for customer deployment activities, driving implementation execution and coordinating with architects, product managers, RD teams, and customer stakeholders.
• Lead complex technical issue resolution and coordinate cross-functional engineering teams when escalations are required.
• Conduct customer acceptance testing and validate deployment success criteria.
• Train customer teams on solution operation, best practices, and troubleshooting procedures.
• Field Documentation Knowledge Management
• Create and maintain installation guides, deployment documentation, configuration records, and troubleshooting playbooks.
• Document lessons learned and best practices to improve future deployment…