AI and Innovation Engineer Intern

The AI Engineer Intern will support the agency’s enterprise modernization, AI and data science initiatives by assisting with the research, design, development, and evaluation of advanced solutions involving cloud-native solutions, AI and Agentic AI, RPA solutions. The intern will work on applied use cases involving Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI, and RPA to enhance decision support, operational efficiency, and innovation across the agency while adhering to security, privacy, and governance standards. The intern will work on designing, building and implementing cloud-native applications, AI solutions, and also help with creating policies, governance for AI with security, privacy, ethics, and regulatory guardrails.

THE INTERN WILL GAIN:

● Hands-on experience working on real-world Cloud, AI and data science projects within a large state agency.

● Exposure to enterprise-scale Cloud, AI architecture, governance, and cloud platforms.

● Opportunity to collaborate with senior architects and technology leaders on emerging Cloud and AI initiatives.

● Development of technical, analytical, and professional skills applicable to AI engineering careers.

Internship Projects and Deliverables:

● Agentic AI Platform implementation

● Modernization of high-risk legacy systems

● Agentic AI solution for one or two agency use cases using GCP, AWS, Azure platforms

● Modernization of one or two legacy systems using cloud-native architecture and implementation

● Develop documents describing design, architecture of AI Systems with prescribed security, privacy, ethical guardrails

To be successful in the program, candidates should demonstrate interest in one or more of the following areas:

● Data Science, Artificial Intelligence & Intelligent Systems – Interest in how AI capabilities, including machine learning and emerging agent-based systems, are applied within enterprise environments to support decision making, automation, and business processes.

● AI-Enabled Platforms & Automation – Interest in how AI services integrate with cloud platforms, workflows, and existing systems to augment IT and business operations.

● Responsible & Governed AI – Awareness of or curiosity about AI governance, ethical considerations, risk management, and policy implications in large organizations.

● Cloud Computing & Modern Platforms - Curiosity about cloud services, platform architectures, and modernization of legacy systems.

● System Integration & APIs - Interest in how systems communicate using APIs, messaging, and integration patterns.

● Data Platforms & Analytics - Exposure to or interest in databases, data platforms, analytics, and data governance concepts.

EDUCATIONAL REQUIREMENTS:

Preference will be given to the following degree programs, as these paths provide essential foundational knowledge in systems, applications, data, and infrastructure—core elements for an AI and Innovation Engineer (current enrollment or recent graduate):

● Computer Science, AI/Machine Learning or Data Science, Applied Artificial Intelligence, Information Systems or Management Information Systems (MIS), Information Technology, Computer Engineering or Electrical Engineering, Data Analytics or Data Science with strong IT foundations, and Software Engineering.

KNOWLEDGE, SKILLS, AND ABILITIES

● Foundational knowledge of Cloud Solutions and Cloud Services offerings, Well Architected Framework and Application Development lifecycle.

● Foundational knowledge of Artificial Intelligence and Data Science concepts.

● Familiarity with Generative AI and Large Language Models (LLMs).

● Understanding of RAG architectures, vector search, and embeddings.

● Exposure to or interest in Agentic AI concepts and autonomous workflows.

● Experience or coursework using Python and common data science libraries (e.g., pandas, NumPy, scikit-learn).

● Basic knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud, especially AI/ML services.

● Ability to analyze problems, synthesize findings, and communicate results clearly in writing and presentations.

PPREFERRED SKILLS:

● Coursework or hands-on experience in Machine Learning, Deep Learning, or Natural Language Processing (NLP).

● Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar (preferred, not required).

● Familiarity with data engineering concepts, APIs, or MLOps fundamentals.

● Interest in public sector technology, responsible AI, data governance, and ethical AI practices.

● Ability to analyze problems, synthesize findings, and communicate results clearly in writing and presentations.

LOCATION AND COMMITMENT:

This position offers a hybrid work arrangement, combining remote and on-site responsibilities at our Austin State Office location. This internship runs from June 1 to August 31 and requires a commitment of approximately 35 hours per week.

This position is temporary in nature and unpaid.