AI Solution Analyst - Global Future Leaders Program (2027)

What You’ll Do

Technical Pre-Sales & Live Demos: Support customer-facing technical discussions, configure and deliver live demos, and help articulate CSAS platform capabilities to both technical and business stakeholders.

Customer Workflow Discovery: Participate in discovery workshops to understand current customer service workflows, identify pain points, and map opportunities for AI-driven transformation.

R&D & Platform Enhancement: Collaborate with the R&D team to refine and extend CSAS platform features based on real-world customer requirements and feedback.

Forward Deployed Engineering (FDE): Work hands-on with customers to configure, integrate, and customize CSAS solutions in on-site or remote deployment scenarios.

Proof of Concept (PoC) Execution: Help design, build, and validate PoCs that demonstrate the value of CSAS in real customer environments.

KPI Instrumentation & Value Tracking: Assist in defining, instrumenting, and tracking KPIs that quantify AI impact on customer service performance and business outcomes.

Field-to-R&D Feedback Loop: Capture field insights, performance data, and customer feedback, and channel them back to R&D to guide roadmap, tuning, and continuous improvement.

What You’ll Learn

How an enterprise-grade, agentic AI customer service platform is designed, sold, customized, and deployed across global customers.

How to translate customer workflows and business problems into AI-driven architectures, PoCs, and production implementations.

How to work at the intersection of technical pre-sales, software engineering, and forward deployed engineering in a fast-moving AI environment.

How to communicate AI and LLM architectures clearly to executives, business stakeholders, and technical teams.

How to instrument, measure, and communicate AI-driven value using KPIs tied to customer service operations and business impact.

Job Requirements: Must Have

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related quantitative engineering discipline from an accredited University (recent / fresh graduate).

Core Software Engineering: Solid hands-on programming proficiency in Python, JavaScript/TypeScript, and SQL, with foundational knowledge of RESTful API design and data integration pipelines.

AI & LLM Foundations: Clear understanding of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) concepts.

Communication & Storytelling: Excellent verbal and written English communication skills, with the ability to explain technical AI architectures to both technical engineers and business executives.

Adaptability & Drive: Strong analytical problem-solving mindset with a willingness to operate across customer-facing pre-sales, hands-on coding, and on-site/remote client implementations.

Nice to Have

Exposure to modern AI agent orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or Model Context Protocol (MCP).

Familiarity with enterprise SaaS developer platforms (e.g., Salesforce, ServiceNow, Zendesk), cloud platforms (AWS, Azure, GCP), and containerization tools (Docker, Kubernetes).

Internship or project experience involving AI/ML models, Natural Language Processing (NLP), or conversational AI platforms.

Multilingual skills (e.g., Mandarin) to facilitate collaboration across global R&D hubs and regional delivery teams.

Currently completing or recently completed a degree from an accredited university (Bachelors, Masters or PhD)

Passion for technology, innovation, and continuous learning

Demonstrated leadership potential through academic, professional, internship, or community involvement

Strong analytical, quantitative, and problem-solving capabilities

Excellent communication and collaboration skills, with the ability to influence and work effectively across global teams

Ability to think strategically, manage ambiguity, and execute with attention to detail

Flexibility to travel as needed (approximately 10-20%)

North America Hiring Time Line Fall 2026

Application Timeline: September 1st through Oct 23rd

Leadership Assessments: Sept-Oct: (Post resume review, top candidates will be selected to complete a Leadership Skills Assessment via SHL (Vendor). NOTE: By applying to this role, if selected for next step, you agree for Lenovo to share your first/last name and email with SHL.

North America LIVE CASE Interview (Virtual/Teams Setting) : Oct 22nd-24th

Leadership Final Interviews LIVE @Lenovo Campus: November 12th-13th @ Lenovo, Morrisville, NC (In Person/Travel Included)

Offers: December

Onboarding: Spring/Summer 2027

Search Roles: GFL26.27 (Search GFL roles in Jobs.le novo.com using this code)