Lead, Applied AI & Innovation
Summary
Technical anchor of Lenovo's Corporate Strategy innovation team: designs, builds and ships agentic AI products (LLM agents, RAG, evaluation) that enable AI-native working internally, owning the architecture end to end — model/platform selection, orchestration, security, integration — while staying hands-on writing production Python.
Salary: -
About the team
The Innovation function within Corporate Strategy identifies, tests and scales new ways for Lenovo to create value with AI, from internal productivity and decision tools to new offerings. The team sits with business, finance and strategy professionals and works across Lenovo's business groups and corporate functions.
This role is the team's technical anchor.
Key responsibilities
Build agentic AI products
• Design, develop and deliver agentic AI products that enable AI-native working for the strategy team, with a clear path to corporate-wide adoption.
• Architect how these products access, organise and apply corporate context (documents, data, systems and institutional knowledge) in a flexible, governed and secure manner.
• Ensure the products generate insightful, decision-grade outputs, and design them to improve and scale as the team's needs and the underlying context grow.
• Own the technical architecture end to end, including model and platform selection, agent orchestration, evaluation, security and integration with Lenovo systems.
• Write production-quality code and remain hands-on throughout; this is not an oversight role.
• Establish standards for responsible AI, data governance and evaluation so that products satisfy IT, security and compliance requirements.
Drive adoption and business outcomes
• Partner with business, finance and strategy colleagues to identify high-value use cases, define success measures and build the business case.
• Translate between executives and engineers: articulate AI capabilities and limitations clearly, and convert business requirements into technical scope.
• Lead products from pilot through user testing to scaled rollout, including change management and enablement for adopting teams.
• Present progress, results and recommendations to senior leadership.
Shape the AI agenda
• Monitor the AI landscape (models, platforms, tooling and regulation) and advise the team on developments relevant to Lenovo.
• Evaluate and manage vendors, cloud platforms and partners; inform build-versus-buy decisions.
• Mentor colleagues on AI tools and practices and raise the team's overall technical fluency.
• Contribute to the innovation roadmap and portfolio prioritisation.
Required experience and qualifications
• 7+ years of professional experience in software engineering, technical product or program management, or AI solutions delivery, including at least 3 years as the accountable owner or lead of technology initiatives.
• A hands-on engineering track record: you have written and shipped production software and continue to code today.
• Recent experience (within the last 2–3 years) deploying AI solutions inside an enterprise, with at least one example that reached real users in production.
• Deep practical expertise in large language models and agentic systems, including agent design and orchestration, retrieval-augmented generation and systematic evaluation.
• Strong Python engineering skills and proficiency with at least one major cloud platform (Azure, AWS or GCP), including APIs, data pipelines and enterprise system integration.
• Working knowledge of the security, access control and data governance requirements of enterprise AI deployment.
• Experience working with multinational companies and global or regional stakeholders; fluent in English with senior business audiences.
• Bachelor's degree in Computer Science, Engineering or a related quantitative field, or equivalent practical experience. A master's degree or MBA is advantageous but not required.
Business and collaboration skills
• Business judgement: frames AI initiatives in terms of value and risk, and recognises when not to build.
• Communicates clearly with non-technical colleagues and senior executives.
• Structured problem-solving: turns ambiguous business questions into well-scoped pilots.
• Manages stakeholders across business groups, IT, legal and compliance in a matrixed organisation.
• Product mindset: prioritises by user value, measures adoption and iterates.