Applied AI Engineer Intern

Conduent delivers mission-critical services and solutions for companies and governments. The Applied AI Engineer Intern will support AI-enabled initiatives within Government Healthcare Solutions by organizing enterprise knowledge, preparing and extracting data, evaluating retrieval and knowledge representations, and documenting experiments and recommendations.

What you'll do:

• Work with a team-provided, sampled, design-only corpus to assess document types, metadata, domain concepts, relationships, and quality issues that affect retrieval; scope will be established with the team
• Build preprocessing and LLM-assisted extraction workflows that transform unstructured design artifacts into candidate structured representations, including concepts, relationships, provenance, and concise summaries, with human validation
• Establish an embeddings/vector-index retrieval baseline as an experiment on the sampled corpus and compare it with richer approaches; the baseline is not intended to serve as a production tester-facing tool or test-authoring pipeline
• Explore knowledge graphs, knowledge maps, and other structured indexes, and use evidence to compare their performance with the vector baseline without assuming that one representation will be superior
• Use sequential LLM-assisted distillation and assimilation to produce a reusable written knowledge digest, or equivalent, layered on top of the index and/or graph for a representative sample selected with the team
• Demonstrate, with supervisor review, that retrieved and distilled knowledge is grounded and reusable through identifiers, provenance, and human-checkable excerpts
• Define and track retrieval and knowledge-quality measures, such as relevance, coverage, precision of retrieved context, redundancy, provenance and groundedness, completeness, consistency, and human validation, including review with QA practitioners
• Document architecture decisions, experiments, results, limitations, failure modes, and recommended next steps, including how Conduent teams can maintain the Azure-based experiments

What they're looking for:

• Currently enrolled in a graduate program, or have equivalent preparation, in Data Science, Computer Science, Natural Language Processing, Information Retrieval, Machine Learning, Artificial Intelligence, Engineering, or a closely related field
• Coursework, project experience, or demonstrated work involving natural language processing, information extraction, vector search, retrieval-augmented generation as an experimental method, knowledge representation, applied AI for unstructured enterprise text, or experimental design and evaluation
• Comfort working with messy, unstructured text and conducting quantitative evaluation and human review—not only developing demonstrations
• Ability and willingness to build and empirically compare multiple representations rather than relying on a single vector index
• Strong written communication skills and the ability to explain technical work clearly to both technical and non-technical audiences
• Ability to work independently in a remote environment while collaborating effectively, incorporating feedback, and providing regular progress updates
• Applicants must be available to work remotely for 20 hours per week for the duration of the fall internship program and should be comfortable balancing independent execution with regular collaboration, feedback, and progress updates
• Familiarity with cloud platforms, particularly Microsoft Azure, is helpful; approved project resources will be provided by Conduent

Benefits:

• Remote work arrangement, with 20 hours per week for the duration of the fall internship program
• Mentorship
• Networking opportunities
• Exposure to senior leadership
• Hands-on experience applying AI engineering concepts to practical enterprise challenges
• Exposure to data preparation, information retrieval, automation, and AI-enabled knowledge management
• Practical experience supporting prototypes, evaluations, and proof-of-concept work
• Experience collaborating with technical and business stakeholders in a remote environment
• Practice documenting results, insights, limitations, and recommendations for future work
• This position, based on business need, may be eligible for a bonus or incentive