About this role
Worldpac seeks an early-career Associate AI Engineer for its Data & Analytics team. Working with experienced engineers and external delivery partners, the engineer will help design, build and support AI-powered chat assistants, workflow automations and integrations with business systems. The position is full-time and on-site at the Oak Brook, Illinois office. Worldpac cannot sponsor H1-B or TN visas now or in the future. The posted salary range is USD $83,000–$111,000 per year.
Responsibilities
- Translate product requirements and user stories into AI/ML solutions with guidance from senior engineers and the Product Manager. Build and test internal chat assistants and automation tools; integrate solutions with databases, APIs and business applications.
- Help build, train and evaluate machine-learning and LLM-based features. Contribute to AI-agent and retrieval-augmented generation (RAG) workflows, support existing agents and automations, troubleshoot issues, and help promote the internal WPChat platform.
- Write documented code, participate in code reviews, document deliverables and collaborate with IT, data, business teams and external vendors.
Required qualifications
- A bachelor’s degree in Computer Science, Engineering, Data Science or a related field, or equivalent education and practical experience, including a bootcamp or strong self-taught portfolio. Recent and upcoming graduates are welcome.
- Foundational Python ability, an understanding of AI/ML and LLM concepts, and hands-on exposure to at least one of: an LLM or AI-framework project, machine-learning project, API integration or chatbot. Coursework, personal projects and capstones count.
- Familiarity with Git, documentation and debugging; strong problem-solving, attention to detail, communication, collaboration and willingness to learn.
Preferred, not required: Exposure to agent frameworks such as LangChain, AutoGen, LangGraph, CrewAI or Flowise; RAG tools such as LlamaIndex or Haystack; cloud or AI platforms; LibreChat, MLOps tools, AI gateways or MCP servers; conversational AI, data privacy and security, relevant software projects, or wholesale distribution, manufacturing, CPG and eCommerce.
Growth: Through mentorship, onboarding, projects and code reviews, the hire can develop production experience over roughly the first 6–18 months with agent orchestration, RAG and NLP, cloud deployment, enterprise integrations, RPA connected to LLM decision layers, MLOps and multichannel conversational AI. These are learning opportunities, not prerequisites.