AI & Data Platform Engineering Intern (Undergraduate)

🏢 wex · all 61 jobs
📍 United States
📅 Posted Sep 17, 2026 · via Himalayas
🏷 AI Engineering, Data Engineering, Data Platform Engineering, Machine Learning Engineering, Software Engineering Intern, Data Engineering Intern +5 more
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WEX is a global commerce platform that has been simplifying the way businesses operate for over 40 years. Our purpose is simple: to reduce administrative burdens, streamline payments, and manage mobility. With a team of over 7,200 professionals across 16 countries.

Our specialties are employee benefits, business payments, and fleet/mobility solutions. We support more than 20 million SaaS accounts, 8 million Health Savings Accounts, and 19+ million vehicles worldwide. We're a growing company with a history of innovation and a focus on our customers, making this a great place to grow your career.

The WEX Summer Internship Program: Learn, Lead, and Make an Impact

Our 13-week paid internship program, running from late May to mid-August, is a chance for you to gain real-world experience and develop your skills. Recruiting begins in September and continues through November at our various locations across the U.S.

You won't just be a bystander; you'll work on impactful projects and contribute to WEX’s mission. We provide mentorship, professional development, and weekly learning experiences to help you build confidence and leadership skills. High-performing interns may even get the chance to lead their own initiatives.

We offer remote, hybrid, and onsite options for flexibility, and our goal is to bring top interns back full-time or offer them extended roles during the school year.

Imagine starting your career with a company that’s building what's next. Your future starts here.
About the Team/Role:

We are seeking a highly motivated and talented undergraduate student in Computer Science, Data Science, Software Engineering, Information Systems, or a related field to join our Data, AI, and Risk Technology (DART), Semantic Foundation, and Enterprise Applications engineering teams as an intern. This is a unique opportunity to contribute to cutting-edge AI/ML applications, Big Data platforms, agentic systems, and Enterprise Semantic Models within the FinTech industry—supporting key business functions across Fraud and Credit Risk, Sales, Service, Marketing, HR, Finance, and Legal.

Working alongside experienced engineers and researchers, you will tackle real-world data engineering and platform challenges using modern technologies such as Python, SQL, Airflow, dbt, PySpark, Snowflake, cloud platforms, and LLMs. Our team is global and remote-first (spanning the U.S., India, and Brazil), operating with agile sprint disciplines and maintaining a strong culture of ownership, learning, and cross-functional collaboration.
How you’ll make an impact:

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Contribute to Impactful Projects: Work on challenging projects that leverage AI/ML to address critical business needs in areas like fraud prevention, credit risk assessment, and real-time, data-driven decision making.

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Build Trusted Data Foundations: Contribute to semantic models and reusable data assets that provide consistent business entities, definitions, and context for analytics, applications, and AI use cases across the enterprise.

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Data Transformation & Pipelines: Develop advanced platforms, SQL queries, and tools to process, ingest, clean, enrich, and optimize core company data—leveraging consuming services, microservices, and DAGs to unlock value for both customers and internal teams.

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Design and implement: AI-assisted workflows that directly optimize our production environment. Apply specification-driven development and declarative system design to build highly scalable, model-driven solution.

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AI Prototyping & Workflow Automation: Help construct and test proof-of-concept AI solutions, automated scripts, basic agentic workflows, and LLM implementations to solve everyday business problems.

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Improve Data Quality & Observability: Help implement automated data-quality checks, monitoring, alerting, and observability capabilities that improve the accuracy, completeness, freshness, and reliability of critical data platforms and pipelines.

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