Forward Deployed Engineer

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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.

Lenovo Solutions & Services Group is running a company-wide AI transformation programme, embedding engineering talent directly inside business functions. Forward Deployed Engineers (FDEs) are the builders at the center of that model.

As an FDE, you will be assigned to a specific business function and work alongside its leaders and teams to identify where AI creates real leverage, then build and deploy practical solutions that fit how work actually gets done. This is not a research or advisory role — you move from discovery to working prototype to deployed solution within sprint cycles, in close partnership with a Domain Leader who provides business direction and context.

The right candidate is energized by driving meaningful change in a business — not just shipping code, but making sure what gets built is genuinely adopted and used. You are comfortable working with typical tech stacks such as Microsoft and ServiceNow as well as building custom AI agents/ solutions on other internal platforms.

Job Responsibilities:

Embed in a business function and work with the Domain Leader and subject matter experts to map workflows, surface pain points, and identify high-value AI opportunities.

Translate business problems into scoped, deliverable use cases — balancing ambition with what is practical to build and adopt.

Build and Deploy

Design and build AI solutions using the right tools for the problem: Microsoft AI and productivity platforms (Copilot Studio, Azure OpenAI, M365), RAG pipelines, agent workflows, automation tooling, and custom development where needed.

Prototype quickly, test with real users, and iterate within short sprint cycles.

Deliver solutions that integrate into existing workflows — not standalone demos.

Drive Adoption and Impact

Own adoption as well as technical delivery — work alongside change resources to help teams actually use what gets built.

Gather feedback post-deployment to improve performance and increase business value over time.

Contribute to patterns and practices that can scale across squads and functions.

Communicate and Collaborate

Bridge business stakeholders, data teams, and platform partners — translating clearly in both directions.

Provide concise, honest updates on progress, risks, and tradeoffs to technical and senior non-technical audiences alike.

Job Requirements:

5+ years in software engineering, solutions engineering, applied AI, or a closely related technical role.

Hands-on experience building and deploying AI, automation, or intelligent workflow solutions in real business settings.

Strong working knowledge of LLMs, prompt design, retrieval-based architectures, orchestration, and agent-based systems.

Comfortable integrating with enterprise APIs, data sources, and workflow platforms.

A genuine drive to see change land — you understand that building the solution is only half the job.

Clear communicator; able to explain technical decisions in plain language to business and leadership audiences.

Preferred

Experience with Microsoft AI platforms: Copilot Studio, Azure OpenAI, M365, Power Platform.

Custom development skills (Python, JavaScript, or similar) for problems that off-the-shelf tooling cannot solve.

Background in technical consulting, solutions architecture, or customer-facing engineering.

Experience with change enablement, user adoption, or process redesign alongside technical delivery.

What Success Looks Like

Working solutions in users’ hands at the end of each sprint — not decks or proofs of concept.

Measurable business outcomes: time saved, processes improved, decisions made faster.

A team that has adopted the tools and can articulate the impact.

A function that can operate and evolve its AI solutions after the engagement ends.