2027 Summer Intern, AI Engineer (Reston, VA)

ICF•Reston, VA

1d•Hybrid

About The Position

ICF is hiring an AI Engineering Intern for a 10-week, full-time internship expected to run from June through August 2027. The role is hybrid in Reston, Virginia, with work onsite two days per week. The intern will support the design, development, testing, and responsible use of AI-enabled solutions, collaborating with technical, data, security, and business or program specialists to turn defined needs into practical, repeatable solutions. Depending on project assignments, work may involve AI application development, data engineering, cloud and platform services, automation, AI governance, or related areas. This is a hands-on learning opportunity with guidance and feedback from experienced team members. ICF does not provide housing or relocation assistance for this position. Assignments may include writing code, preparing and evaluating data, prototyping AI-assisted workflows, testing controls and outputs, documenting technical processes, and communicating findings to technical and nontechnical audiences. The intern will use approved tools and data, follow applicable privacy, security, and governance requirements, and document assumptions and limitations. AI-generated outputs that may inform business or program decisions remain subject to appropriate human review.

Requirements

At least 30 completed college credit hours by the start date in computer science, data science, information systems, engineering, analytics, cybersecurity, or a related field.
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 technical and nontechnical audiences.
Effective organization and time-management skills, including the ability to prioritize work, manage defined assignments, meet agreed deadlines, ask questions, and communicate blockers when needed.
Ability to work independently and collaborate effectively with distributed, cross-functional teams.
A practical and adaptable approach to learning and problem-solving, including openness to feedback and willingness to revise work and learn unfamiliar tools, technologies, or business domains.
Professional judgment when working with data, technical tools, documentation, and AI-generated outputs, including attention to review, accuracy, privacy, security, and governance considerations.

Nice To Haves

A completed bachelor's degree and enrollment verification or at least 9 completed graduate-program credit hours in a related field.
Experience with programming or scripting languages such as Python, PowerShell, JavaScript, SQL, or comparable languages, including scripting, data manipulation, querying, analysis, or reusable code development.
Experience with technical projects involving coding, data, artificial intelligence, automation, cloud technology, or systems work through coursework, personal projects, research, internships, employment, or other applied experience.
Familiarity with databases, data schemas, data pipelines, extract-transform-load processes, and 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.

Responsibilities

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 for 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.
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 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.