AI & Business Systems Automation Intern

About the Role

This is a 12-week, hands-on, project-oriented internship focused on improving real-world business operations through artificial intelligence, software integration, data analysis, and workflow automation. Interns will work with employees to identify repetitive tasks, streamline workflows, integrate AI into existing business systems, and develop automation solutions. The objective is to implement useful, reliable automations that employees can incorporate into their daily operations.

Work Location and Arrangement

• On-site attendance required in Houston, TX 77047.
• Remote and hybrid work arrangements are not available.

Key Responsibilities

• Business Process Analysis and Automation
• Understand existing workflows and operational challenges with employees and department managers.
• Identify processes benefiting from automation.
• Evaluate opportunities using AI, Python, APIs, SQL, and workflow automation tools.
• Document processes and recommend solutions.
• Prioritize projects based on business value.
• Establish baseline metrics and measure improvements.
• Applied Artificial Intelligence and Intelligent Automation
• Develop applications using AI tools, large language models (LLMs), and approved AI APIs.
• Automate document processing, email classification, information extraction, summarization, and report generation.
• Build AI-assisted workflows to connect applications and reduce manual data entry.
• Combine AI with conventional programming, business rules, and structured data.
• Test AI outputs for accuracy, consistency, and reliability.
• Implement human review and approval procedures.
• Evaluate existing AI products and automation platforms.
• Software Integration and Business Systems
• Work with existing ERP, CRM, accounting, inventory management, logistics, laboratory, and manufacturing systems.
• Develop integrations using REST APIs, webhooks, SQL, Python, and approved automation platforms.
• Automate data exchange between systems.
• Extract, transform, validate, and organize operational data.
• Develop automated reports, notifications, alerts, and dashboards.
• Troubleshoot integration issues.
• Document integrations and workflows.
• Customer Service Automation
• Automate order processing, email management, and customer communications.
• Develop tools to categorize emails and extract customer, order, and delivery information.
• Assist with order-status inquiries and communication workflows.
• Develop automated workflows to generate Bills of Lading (BOLs) and related shipping documents.
• Automate the transfer of shipment information into shipping forms.
• Reduce manual data entry by integrating order information with document generation tools and business systems.
• Dispatch and Logistics Automation
• Improve dispatch scheduling, shipment tracking, and delivery coordination.
• Automate shipment-status notifications and interdepartmental communications.
• Consolidate logistics data.
• Develop and implement automated processes for creating, updating, and distributing Bills of Lading (BOLs), packing lists, and shipping labels.
• Integrate shipping-document workflows with order management, inventory, and transportation systems.
• Implement automated validation checks for shipping documents.
• Automate document storage, naming, retrieval, and distribution.
• Explore AI-assisted document processing for shipment information extraction.
• Develop reports to monitor delivery performance and operational bottlenecks.
• Purchasing and Inventory Management
• Develop tools to compare supplier quotations and purchasing terms.
• Automate the organization and analysis of supplier information.
• Analyze inventory levels and consumption patterns.
• Create alerts for low inventory and unusual pricing changes.
• Assist with inventory reporting and supplier performance analysis.
• Sales and CRM Automation
• Improve CRM data quality and automate record maintenance.
• Develop automated customer follow-up reminders and sales activity notifications.
• Use AI to summarize customer interactions.
• Automate sales pipeline reporting and performance dashboards.
• Laboratory and Manufacturing Automation
• Organize laboratory testing, quality-control, and manufacturing data.
• Automate routine calculations, data consolidation, and report preparation.
• Develop tools to identify missing data and operational trends.
• Assist with production reporting and analysis of process efficiency.
• Accounting and Administrative Automation
• Develop tools to extract information from invoices, purchase orders, and receipts.
• Automate routine data entry and reconciliation workflows.
• Identify discrepancies for review.
• Develop administrative reports and exception notifications.
• Improve speed and accuracy of accounting processes.
• Testing, Implementation, and Documentation
• Develop prototypes and working solutions.
• Test solutions against business scenarios.
• Refine implementations based on user feedback and performance.
• Document source code, integrations, and operating procedures.
• Follow company requirements for confidentiality, data security, and change management.
• Demonstrate completed work to stakeholders.
• Prepare technical handover materials.

Requirements & Tech Stack

• Python programming
• SQL, relational databases, and data manipulation
• APIs, JSON, and basic software integration concepts
• Interest in applied AI, LLMs, machine learning, or workflow automation
• Analytical thinking and problem-solving skills
• Ability to communicate effectively
• Willingness to learn existing business systems
• Attention to detail, initiative, reliability, and a results-oriented mindset
• Preferred: Experience with ERP, CRM, accounting, inventory, logistics, or manufacturing software integration.
• Preferred: Experience using AI APIs, LLMs, prompt engineering.
• Preferred: Familiarity with automation platforms (e.g., Microsoft Power Automate, n8n, Zapier).
• Preferred: Experience with Python libraries (pandas).
• Preferred: Familiarity with Git, version control, testing, and software documentation.
• Preferred: Exposure to cloud services, scheduled jobs, database integrations, or application deployment.
• Preferred: Knowledge of machine learning, forecasting, anomaly detection, or optimization.
• Preferred: Previous internships, academic projects, research, or personal projects involving software development, AI, or automation.
• Preferred: Ability to demonstrate a working project, code sample, or relevant technical portfolio.

Qualifications

• Currently enrolled as a junior, senior, or graduate student in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems, or a related discipline.