Technical Expertise

• SQL fundamentals — comfortable writing queries against structured data, not just describing them

• Exposure to LLM APIs (e.g., OpenAI, Azure OpenAI, Anthropic) and at least tutorial-level familiarity with one orchestration framework (LangChain, LlamaIndex, or similar)

• Git basics — comfortable with branching and reviewing code as part of a team workflow

• Ability to reason about data quality, duplication, and freshness

• Fetch and ingest data from live external sources (APIs and web sources) into a structured pipeline — handling formats, rate limits, and failures, not just calling a pre-built connector

• Design and build the schema and storage layer your pipeline writes to, in collaboration with data engineering

• Build and test AI components — embeddings, retrieval logic, prompts — using established patterns and tools

Communication & Collaboration

• Communicates technology-related updates and requirements to other departments and contributes to presentations for senior management.
• Collaborates with research and development teams, product management, and strategic analysts to support ongoing projects.

Leadership & Management

• Partners with Business Units to provide reliable intelligence, validated technology options, and insights on enterprise and industry trends.
• Supports technology project teams by coordinating specific tasks, assisting with day-to-day operations, and contributing to the successful delivery of solutions.
• Assists in collaborative efforts with academic research teams, practicums, internships, and vendor POCs.

External Relationships & Partnerships

• Supports vendor evaluations and contributes to collaborations with vendors.
• Assists as a liaison between academic institutions, professional organizations, and research groups as needed.

Other

• Support the Academic Corporate Engagement efforts to develop research and educational talent, with a focus on enhancing health tech knowledge and skills.
• Complete all responsibilities and goals outlined in the internship program.
• Complete all special projects and other duties as assigned.
• Must be able to perform duties with or without reasonable accommodation.

This job description is intended to describe the general nature and level of work being performed in this internship. It is not an exhaustive list of responsibilities, duties, and skills required and does not constitute an employment agreement. This job description is subject to change as Cotiviti’s needs and requirements of the internship evolve.

• Currently pursuing or recently completed an advanced degree in healthcare, technology, or a related field (e.g., Biomedical Informatics, Computer Science) with preference of a PhD.
• Demonstrated interest or experience in AI, healthcare technology, or informatics research.
• Strong foundational knowledge in generative AI model development, architectures, and vector databases.
• Hands-on experience with working with Machine Learning and Deep Learning models. Experience with LLM/RAG models and LLM fine-tuning is a plus.
• Hands-on experience working with cloud services (AWS/Azure), large data sets, and building data pipelines for ML solutions. Experience with vector embeddings and databases is a plus.
• Ability to work collaboratively and communicate effectively with cross-functional teams.

• Communicating with others to exchange information.
• Assessing the accuracy, neatness, and thoroughness of the work assigned.

• Remaining in a stationary position, often standing or sitting for prolonged periods.
• Repeating motions that may include the wrists, hands, and/or fingers.
• Must be able to provide a dedicated, secure work area.
• Must be able to provide high-speed internet access/connectivity and office setup and maintenance.
• No adverse environmental conditions are expected.