Responsibilities
- Design end-to-end architectures and reusable blueprints for generative AI, agentic AI, RAG, predictive AI/ML, and hybrid cloud-edge applications.
- Lead hands-on prototypes, proofs of value, minimum viable products, and production-grade AI application implementations.
- Apply AI full-stack development practices across user experience, APIs, orchestration, model integration, retrieval, evaluation, deployment, and monitoring.
- Use and extend the UDS cloud platform, UDC client agents, and other CSW assets for secure cloud-to-device AI integrations.
- Architect resilient, multi-tenant, cloud-native services and define scalability, availability, disaster recovery, performance, observability, and cost targets.
- Lead capacity planning, load and stress testing, bottleneck analysis, caching, asynchronous processing, and model-inference optimization.
- Embed security, privacy, responsible AI, identity, authorization, encryption, data governance, tenant isolation, and supply-chain controls into solution designs.
- Define MLOps/LLMOps, automated evaluation, release, rollback, model-update, incident-response, and production-readiness approaches.
- Partner with segment, product, UX, data, security, cloud, device, and engineering teams through discovery sessions, architecture reviews, implementation, troubleshooting, and production delivery.
- Establish reusable architecture patterns, technical standards, reference implementations, and platform improvements that accelerate adoption across teams.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field; a Master’s degree is a plus.
- 8+ years of experience in software engineering, solution architecture, cloud engineering, or related technical roles, including significant cloud-based application delivery.
- Demonstrated experience designing and implementing production AI/ML or generative AI applications from concept through deployment and operations.
- Strong competency in AI full-stack development, including application engineering, model integration, retrieval and agentic patterns, evaluation, deployment, and observability.
- Deep knowledge of cloud architecture, distributed systems, APIs, microservices, containers, Kubernetes, event-driven design, data stores, caching, and asynchronous processing.
- Hands-on proficiency in Python and at least one additional language such as TypeScript/JavaScript, Java, C#, or Go.
- Experience with AI frameworks and services such as PyTorch, TensorFlow, Hugging Face, ONNX Runtime, LangChain, LlamaIndex, or Semantic Kernel.
- Experience with at least one major public cloud platform and its AI, data, networking, security, monitoring, and deployment services.
- Proven ability to analyze and improve application and infrastructure performance at scale.
- Strong written and verbal communication, architecture documentation, stakeholder management, and technical leadership skills.
- Preferred experience includes hybrid cloud-device AI, telemetry, remote configuration, real-time messaging, secure client agents, enterprise SaaS, multi-tenant architecture, identity platforms, RAG, vector search, knowledge graphs, AI agents, multimodal models, small language models, model optimization, hardware-accelerated inference, developer platforms, SDKs, threat modeling, privacy engineering, and responsible AI governance.
- Ability to work effectively with globally distributed cross-functional teams and lead through influence.
Tech Stack
Categories
About Lenovo
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. Guided by its vision of “Smarter Technology for All”, Lenovo is executing a Hybrid AI strategy that spans Personal AI – one personal AI, multiple devices; and Enterprise AI – helping customers turn data into insights and value. This strategy is delivered through the Group’s commitment to world-class innovation and a full-stack AI portfolio, including devices (PCs, workstations, smartphones, tablets, accessories), infrastructure solutions (server, storage, edge, high performance computing and software defined infrastructure), as well as software, solutions, and services. With a global footprint spanning 21 research and development locations in 11 markets, and a global supply chain including more than 30 manufacturing sites across 10 markets, Lenovo is widely recognized for its operational excellence, including ranking #8 in the Gartner Supply Chain Top 25. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). To find out more visit https://www.lenovo.com, and read about the latest news via our StoryHub at https://news.lenovo.com/. To learn more about our career opportunities, visit our careers page at http://jobs.lenovo.com/.