AI Application Development

Lenovo•Morrisville, NC

12h•Hybrid

About The Position

Lenovo is seeking a highly motivated, entry-level AI Developer to join its US engineering team in Morrisville, North Carolina, under a hybrid work policy. The role is intended for recent graduates or early-career candidates with a strong software engineering foundation and hands-on AI/ML or Generative AI exposure through internships, research, academic projects, or personal projects. The target start date is January 2027. The developer will design and build enterprise AI applications and product capabilities using technologies such as LLMs, RAG, AI agents, tool and function calling, embeddings and vector search, and AI workflow orchestration. This is an applied engineering role focused on real enterprise products rather than purely AI research. The developer will collaborate with product managers, architects, developers, business stakeholders, and engineering teams across the solution lifecycle. The position offers the opportunity to grow toward a Forward Deployed Engineer-style role combining technical execution, business understanding, customer communication, rapid problem solving, and end-to-end ownership.

Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related technical field.
Recent graduate or early-career candidate with strong academic, internship, research, or project experience.
Strong programming fundamentals and hands-on experience in Python.
Hands-on project, research, or internship experience in at least one AI-related area, such as LLMs, Generative AI applications, RAG, AI agents, AI chatbot or conversational AI, NLP, machine learning, embedding or vector search, tool or function calling, or AI automation.
Ability to clearly explain the architecture, implementation, challenges, and results of AI or software projects personally completed.
Good understanding of software engineering fundamentals, including APIs, databases, debugging, source control, and the software development lifecycle.
Strong learning ability and curiosity about new AI technologies.
Strong problem-solving skills and willingness to work through ambiguous problems.
Good verbal and written communication skills and ability to collaborate with technical and non-technical stakeholders.
Strong ownership mindset and willingness to learn business processes in addition to technology.
Ability to work effectively in a global, cross-functional engineering environment.

Nice To Haves

Master’s degree in Computer Science, AI, Machine Learning, Data Science, or a related field.
Internship or project experience building production-oriented LLM or Generative AI applications.
Experience with frameworks or technologies such as LangChain, LangGraph, AutoGen, Hugging Face, PyTorch, or similar AI development frameworks.
Experience with RAG pipelines, vector databases, embeddings, agent workflows, or tool and function calling.
Experience with backend development using Python frameworks such as FastAPI or Flask.
Familiarity with relational databases, SQL, REST APIs, cloud platforms, Docker, or Kubernetes.
Experience developing and evaluating AI prototypes and converting prototypes into usable applications.
Exposure to LLM evaluation, prompt evaluation, test datasets, or AI observability.
Experience working directly with users, customers, product teams, or business stakeholders through internships, university projects, startup experience, or other activities.
Demonstrated ability to independently explore an unfamiliar problem, quickly build a prototype, collect feedback, and iterate on the solution.
Interest and potential to grow toward a Forward Deployed Engineer role combining engineering, product thinking, business understanding, and stakeholder engagement.
Mandarin Chinese communication skills, due to frequent collaboration with China-based engineering teams.

Responsibilities

Design, develop, test, and enhance enterprise AI applications and AI-enabled product capabilities.
Build solutions involving LLMs, RAG, AI agents, prompt engineering, tool and function calling, vector and embedding search, and AI workflow orchestration.
Develop backend services, APIs, data integrations, and other components that connect AI capabilities with enterprise systems.
Participate in AI evaluation, testing, debugging, and performance improvement to improve solution quality, reliability, latency, and user experience.
Work with product managers, architects, business stakeholders, and engineering teams to understand business problems and translate requirements into practical technical solutions.
Participate in requirement discussions, solution design, technical reviews, demonstrations, user acceptance testing support, and production deployment.
Prototype and evaluate new AI technologies and determine their feasibility for real business scenarios.
Troubleshoot technical and production issues and continuously improve application stability and engineering quality.
Develop an understanding of business processes and user journeys, not just individual technical tasks.
Gradually take greater ownership of solutions from problem definition and prototyping through implementation and delivery.
For candidates demonstrating strong technical and communication capabilities, develop toward an FDE role by partnering directly with stakeholders, exploring problems, prototyping solutions, and driving AI use cases from concept to production.