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Temporary Intern - Agentic AI & Neural-Symbolic Systems (Healthcare)

Cotiviti
United States
May 01, 2026

Temporary Intern - Agentic AI & Neural-Symbolic Systems (Healthcare)
Job Locations

US-Remote
ID

2026-19075


Category
Engineering/IT

Position Type
Full-Time



Overview

We are looking for two highly motivated undergraduate interns to join our team working on next-generation Agentic AI platforms and neural-symbolic systems in the healthcare domain. This is not a passive internship. You will work on real systems that support complex, high-stakes use cases where reasoning, compliance, and explainability matter. You'll collaborate closely with engineers, data scientists, and product teams to help shape how AI is deployed in production environments.



Responsibilities

    Agentic Framework Evaluation
  • Design and run evaluations for LLM-based agents (quality, reliability, safety)
  • Analyze agent behavior and identify failure modes
  • Propose improvements based on empirical results
  • Agentic Platform Development
  • Build and enhance components such as tools, skills, memory systems, and MCP integrations
  • Improve orchestration, observability, and developer experience
  • Prototype new capabilities for real-world workflows
  • Neural-Symbolic AI (Healthcare Focus)
  • Explore approaches combining LLMs with rules, knowledge graphs, or symbolic reasoning
  • Work on use cases requiring auditability and explainability (e.g., claims, policy logic)
  • Help bridge probabilistic AI with deterministic systems
  • Forward-Deployed Engineering Experiments
  • Partner closely with internal stakeholders or pilot users
  • Rapidly prototype and iterate on solutions in real-world contexts
  • Help define patterns for scaling adoption of agentic systems '

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



Qualifications

  • Currently pursuing a Bachelor's degree (Freshman-Senior) in related field
  • Hands-on experience with Python or similar programming languages
  • Familiarity with LLMs / GenAI (e.g., building projects with OpenAI, Claude, Gemini, or open-source models)
  • Strong curiosity and willingness to learn quickly in ambiguous environments
  • Ability to break down problems and iterate through experimentation

Cognitive/Mental Requirements:

  • Communicating with others to exchange information.
  • Problem-solving and thinking critically.
  • Completing tasks independently.
  • Interpreting data.
  • Making timely decisions in the context of a workflow.
  • Maintaining focus.
  • Assessing the accuracy, neatness and thoroughness of the work assigned.
  • Learning new tasks and completing tasks in situations that have a speed or productivity quota.
  • Remembering and adhering to processes and protocols.

Physical Requirements and Working Conditions:

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

Hourly compensation ranges from $20 to $25 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.

Since this job will be based remotely, all interviews will be conducted virtually.

Date of posting:5/05/2026

Applications are assessed on a rolling basis. We anticipate that the application window will close on 5/25/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.

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