Associate AI Engineer

Please note: We are unable to sponsor H1-B's or TN's now or in the future. About The Role This is an early-career role designed for a new or recent graduate who is excited to build a career in applied AI. You'll join our Data & Analytics team and work alongside experienced engineers and external delivery partners to help design, build, and support AI-powered solutions — including chat assistants, workflow automation, and integrations with our business systems. You won't be expected to know everything on day one. We'll invest in your growth through mentorship, hands-on projects, code reviews, and structured onboarding. What matters most is a solid foundation in programming and AI concepts, genuine curiosity, and the drive to learn quickly. If you've built things in school, an internship, a bootcamp, or on your own — and you're eager to do it in a production environment with people who will help you level up — we'd like to hear from you. What You'll Do You'll start with well-scoped tasks and grow toward more independent work as you develop. Day to day, you will: • Help translate product requirements and user stories into AI/ML solutions, with guidance from senior engineers and the Product Manager • Contribute to building and testing AI chat assistants and automation tools for internal teams, in collaboration with senior engineers and external partners • Assist in integrating AI solutions with existing databases, APIs, and business applications • Help build, train, and evaluate machine-learning and LLM-based features, learning our production, quality, and security standards as you go • Contribute to agentic and retrieval-augmented (RAG) workflows using frameworks such as LangChain or similar — beginning with guided tasks and building toward independence • Support and help maintain existing AI agents, tools, and automations, including troubleshooting with support from the team • Write clean, well-documented code and take part in code reviews to build strong engineering habits • Help support and promote our internal AI chat platform (WPChat) across the organization • Document what you build, and stay current with AI/ML developments — sharing what you learn with the team • Collaborate across IT, data, and business teams, and partner with external vendors on delivery How You'll Grow — What You'll Learn Here These are skills you'll develop on the job with mentorship — not prerequisites. Over roughly your first 6–18 months, you can expect to gain hands-on, production experience with: • Agent orchestration frameworks (LangChain, LangGraph, or AutoGen) and patterns such as ReAct and plan-and-execute, including memory and human-in-the-loop flows • Retrieval-augmented generation (RAG) and NLP tooling — e.g., LlamaIndex, Haystack, PyTorch, scikit-learn • Deploying AI solutions on cloud platforms (AWS, Azure, or GCP) and platform tools such as Vertex AI, Amazon Bedrock, or Azure AI Foundry • Working with AI gateways (e.g., Portkey, Kong) and MCP servers that connect to enterprise systems (Oracle, Workday, Salesforce, ServiceNow, Jira) • Building and integrating RPA workflows and connecting them to LLM decision layers • MLOps practices for deploying and monitoring models, and building conversational AI across channels (web chat, and potentially voice, SMS, and email) What We're Looking For The essentials — this is what we actually require: • A bachelor's degree in Computer Science, Engineering, Data Science, or a related field — or an equivalent combination of education and practical experience (including bootcamps or a strong self-taught portfolio). Recent and upcoming graduates are welcome. • Foundational programming ability in Python, demonstrated through coursework, internships, academic or personal projects, bootcamp work, or open-source contributions • A working understanding of core AI/ML and large language model (LLM) concepts — how they work and where they're used — from classes, projects, or self-study • Hands-on exposure to at least one area relevant to the role: building something with an LLM or an AI framework (e.g., LangChain), a machine-learning project, an API integration, or a chatbot. A class, capstone, or personal project counts. • Comfort with engineering fundamentals: version control (Git), reading documentation, and debugging • Strong problem-solving skills, attention to detail, and a genuine eagerness to learn • Clear communication and a collaborative, team-oriented mindset Nice To Have (Bonus, Not Required) Any of these will strengthen your application, but none are expected of an early-career candidate: • Any hands-on exposure to LLM agent frameworks (LangChain, AutoGen, LangGraph, CrewAI, Flowise) or RAG tools (LlamaIndex, Haystack) • Any experience with a cloud platform (AWS, Azure, GCP) or an AI platform tool (Vertex AI, Bedrock, Azure AI Foundry) • Exposure to LibreChat, MLOps tooling, AI gateways (Portkey, Kong), or MCP servers • Coursework or projects