Co-op - Agentic AI Developer

Labcorp•Durham, NC

3d•Hybrid

About The Position

Labcorp is seeking an Agentic AI Developer Co-op to join the Office of the Chief AI Officer (CAIO) in Burlington or Durham, North Carolina, with a hybrid work schedule. The co-op will work alongside senior engineers and data scientists to build, test, and deploy agentic AI systems and contribute to production workflows in a regulated healthcare and life sciences environment. The role includes hands-on exposure to agent development, AI safety and red teaming, governance, and evaluation of AI technologies and partners. The co-op will contribute to enterprise AI agents and related infrastructure using agentic frameworks, cloud AI platforms, frontier foundation models, containerized deployments, and CI/CD practices. Work will include developing tool integrations, retrieval-augmented generation pipelines, guardrails, observability, evaluation processes, and governance materials. The position is a paid co-op scheduled for January through May 2027, with an option for back-to-back Spring and Summer 2027. The work schedule is Monday through Friday, 40 hours per week. The position is not eligible for visa sponsorship now or in the future.

Requirements

Currently enrolled in a Bachelor's or graduate degree program in Computer Science, Software Engineering, Data Science, Cybersecurity, Information Systems, or a related field.
Strong written and verbal communication skills.
Ability to show initiative and work independently under general supervision.
Interest in learning how agentic AI is built, deployed, and governed in a regulated enterprise.

Nice To Haves

At least one month of familiarity with Python for software development, automation, or machine learning.
At least one month of familiarity with cloud platforms such as AWS or Azure and services such as Bedrock, SageMaker, or AWS AI DLC.
At least one month of familiarity with Docker, Git, and collaborative software development practices.
At least one month of coursework or project experience in distributed systems, cybersecurity, software engineering, multi-agent systems, or reinforcement learning.
Interest in large language models, prompt engineering, or transformer architectures; exposure to OpenAI API, Anthropic API, Hugging Face, or LangChain.
Interest in agentic AI concepts such as tool use, function calling, multi-step planning, chain-of-thought reasoning, or autonomous workflow execution.
Interest in AI safety, AI security, adversarial testing, or responsible AI; familiarity with OWASP Top 10 for LLMs or prompt injection concepts.
Preferred candidates are sophomore, junior, or graduate students currently enrolled in a relevant degree program.

Responsibilities

Contribute to developing AI agents with agentic frameworks to automate complex, multi-step enterprise workflows.
Help implement tool-calling architectures, function-calling interfaces, and MCP integrations for controlled, auditable interaction with APIs, databases, and external services.
Support retrieval-augmented generation pipelines using vector databases to ground agent responses in enterprise data.
Assist with AI red teaming, including prompt injection, jailbreak resistance, tool-use abuse, and multi-turn manipulation testing.
Help build and test runtime guardrails, validators, content filters, and human-in-the-loop approval gates.
Support benchmarking and evaluation of foundation models for task accuracy, latency, cost, safety, and failure modes.
Contribute to agent observability and tracing, including structured logging, token-level attribution, decision audit trails, and cost tracking.
Prototype agentic solutions on cloud AI platforms using containerized deployments, serverless architectures, and CI/CD pipelines.
Support technical due diligence of AI startups and emerging agentic technology partners, including assessment of architecture, safety, and enterprise integration feasibility.
Contribute to AI governance practices, including model onboarding documentation, agent risk assessments, responsible AI compliance, and alignment with healthcare and life sciences regulatory requirements.