2027 Summer Intern, AI Engineer (Reston, VA)

ICF is seeking an AI Engineering Intern to support the design, development, testing, and responsible use of AI-enabled solutions. Working with technical, data, security, and business or program specialists, you will help translate defined needs into practical, repeatable solutions. Depending on the assignment, your work may focus on AI application development, data engineering, cloud and platform services, automation, AI governance, or a combination of these areas. This is a hands-on learning opportunity with guidance and feedback from experienced team members. You may write code, prepare and evaluate data, prototype AI-assisted workflows, test controls and outputs, document technical processes, and communicate findings to technical and nontechnical audiences. This is a 10-week, full-time internship expected to begin in June and end in August.  This role will be hybrid from Reston, VA (2x per week). At this time, we are unable to provide housing nor relocation assistance for this position.      Potential Areas of Alignment Applied AI and intelligent automation: Build or enhance workflows that use approved large language models, machine learning, APIs, agentic tools, or automation technologies. AI and data engineering: Collect, clean, validate, transform, and combine approved structured or unstructured data for AI applications, analytics, databases, or reporting. Enterprise AI platforms and governance: Support secure and responsible AI environments, including access controls, data protection, usage oversight, validation, documentation, and lifecycle practices. Business- or domain-focused solutions: Apply AI engineering skills to operational, corporate, client, or program needs in collaboration with subject matter experts. What You Will Do Collaborate with technical and business or program stakeholders to understand user needs, workflows, requirements, assumptions, constraints, and success criteria. Write, test, and maintain code or scripts to support data processing, AI applications, integrations, automation, validation, or reporting. Prepare and evaluate approved datasets, investigate missing or inconsistent information, and document data sources and processing steps. Help prototype AI-enabled solutions using approved models, APIs, cloud services, low-code tools, or related technologies. Create test cases and evaluate results against source data, expected outcomes, control requirements, or established baselines; record errors, risks, and limitations. Support responsible AI, privacy, security, and governance practices, including appropriate data access, human review, documentation, and use of approved tools. Use version control and team development practices to organize code, configuration, documentation, and incremental changes. Prepare clear technical documentation, runbooks, demonstrations, analyses, or presentations so others can understand, reproduce, and build on the work. Participate in project check-ins and reviews, communicate progress and blockers, track assigned work, and incorporate feedback. Recommend practical improvements to workflows, tools, controls, data quality, testing, or user experience. What You Bring We welcome skills developed through coursework, personal projects, student research, prior internships, employment, or other applied learning. You do not need experience with every technology or focus area listed in this description. Basic Qualifications 30-completed college credit hours by start date in computer science, data science, information systems, engineering, analytics, cybersecurity, or a related field. Preferred Skills and Experience A completed bachelor’s degree and enrollment verification or 9 credit hours completed in a graduate program related to computer science, data science, information systems, engineering, analytics, cybersecurity, or a related field. Experience with programming or scripting languages such as Python, PowerShell, JavaScript, SQL, or comparable languages, including experience with scripting, data manipulation, querying, analysis, or reusable code development. Experience completing technical projects involving coding, data, artificial intelligence, automation, cloud technology, or systems work through coursework, personal projects, research, internships, or other applied experience. Familiarity with databases, data schemas, data pipelines, and extract, transform, and load processes, as well as structured configuration formats such as JSON and YAML. Exposure to artificial intelligence and machine learning concepts, including large language model applications, agentic workflows, computer vision, natural language processing, or model evaluation. Familiarity with APIs, cloud platforms, enterprise data tools, low-code platforms, workflow automation, or business intelligence tools such as Azure, Power Platform, or Power BI.  Experience using Git, Claude Code, or another version-control system, including familiarity with collaborative development, code review, or other review-based workflows. Knowledge of or interest in responsible AI, data privacy, information security, identity and access management, data classification, and AI or data governance. Strong analytical and problem-solving skills, including the ability to test assumptions, evaluate technical outputs, identify limitations, and review work for accuracy and completeness. Strong written and verbal communication skills, including the ability to document technical work, communicate progress or changes, and explain technical concepts to both technical and nontechnical audiences. Effective organization and time management skills, with the ability to prioritize work, manage defined assignments, meet agreed deadlines, ask thoughtful questions, and seek guidance or communicate blockers when needed. Ability to work independently while collaborating effectively with distributed, cross-functional teams. A practica