Labcorp is a global leader in laboratory services, providing the insights and answers that help healthcare providers, patients, researchers, pharmaceutical companies and health systems make confident decisions and improve outcomes. Through our unparalleled science, data, technology and laboratory network, we advance diagnostics, accelerate innovation and help address some of the world’s most important health challenges. As we shape the future of healthcare, we are leveraging advanced technologies, intelligent digital solutions and data-driven innovation across our operations to enhance how work gets done and deliver greater value to customers and patients. With our global scale and deep expertise, you’ll have the opportunity to do meaningful work, grow your career and make a real impact on people’s health around the world. Together, we’re improving health and improving lives.
Labcorp is seeking an Agentic AI Developer Co-op to join our Office of the Chief AI Officer (CAIO) Team located in Burlington, NC or Durham, NC with the flexibility of a Hybrid work schedule!
Work Schedule Days/Hours: Monday through Friday / 40hrs per week
Job Responsibilities:
- Contribute to the development of AI agents using agentic frameworks (LangChain, LangGraph, CrewAI, AutoGen, or custom orchestration layers) that automate complex, multi-step business workflows across the enterprise
- Help implement tool-calling architectures, function-calling interfaces, and MCP (Model Context Protocol) integrations that allow agents to interact with enterprise APIs, databases, and external services in a controlled and auditable manner
- Support the build-out of retrieval augmented generation (RAG) pipelines with vector databases (Pinecone, Weaviate, pgvector, OpenSearch) to ground agent responses in authoritative enterprise data and reduce hallucination in high-stakes contexts
- Assist with AI red teaming exercises including adversarial prompt injection testing, jailbreak resistance evaluation, tool-use abuse scenarios, and multi-turn manipulation testing to help identify vulnerabilities before agents reach production
- Help build and test runtime guardrails, input/output validators, content filters, and human-in-the-loop approval gates that enforce safe agent behavior within a multi-layer defense-in-depth architecture
- Support benchmarking and evaluation of frontier foundation models (GPT-4, Claude, Llama, Gemini, Mistral, and emerging open-source models) for agentic use cases, measuring task completion accuracy, latency, cost, safety, and failure modes
- Contribute to observability and tracing infrastructure for agent execution including structured logging, token-level attribution, decision audit trails, and cost tracking across multi-agent workflows
- Prototype agentic solutions on cloud AI platforms (AWS Bedrock, SageMaker, AWS AI DLC, Azure AI) using containerized deployments (Docker, Kubernetes), serverless architectures, and CI/CD pipelines
- Support evaluation of AI startups and emerging agentic technology partners, helping with technical due diligence on architectures, safety postures, and enterprise integration feasibility
- Contribute to AI governance practices including model onboarding documentation, agent risk assessments, responsible AI compliance, and alignment with regulatory requirements in healthcare and life sciences
Minimum Qualifications:
- Current enrollment in a Bachelor's or Graduate degree program in Computer Science, Software Engineering, Data Science, Cybersecurity or Information Systems
Preferred Qualifications:
- 1-month plus familiarity with Python for software development, automation, or machine learning
- 1-month plus familiarity with cloud platforms (AWS, Azure) and services like Bedrock, SageMaker, or AWS AI DLC
- 1-month plus familiarity with containerization (Docker), version control (Git), and collaborative software development practices
- 1-month plus coursework or projects in distributed systems, cybersecurity, software engineering, multi-agent systems, or reinforcement learning
Additional Job Standards:
- Interest in large language models, prompt engineering, or transformer architectures (experience with OpenAI API, Anthropic API, Hugging Face, or LangChain)
- Interest in agentic AI concepts including 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)
- Strong communication skills; both written and verbal
- Show initiative and the ability to work independently under general supervision
- Eagerness to learn how agentic AI is built, deployed, and governed inside a regulated enterprise where safety and reliability are non-negotiable
About the Team:
Labcorp is becoming an AI-native life sciences company. The Office of the Chief AI Officer (CAIO) leads this transformation across the entire enterprise, improving the customer experience, enhancing productivity, and transforming how work gets done across the organization. Building AI agents safely, responsibly, and at enterprise scale is one of the most important technical challenges in the company. If you want to be part of a team that is figuring out how to build and deploy agentic AI in a regulated, high-stakes healthcare environment where safety and trust are not optional, this is the role.
This co-op role sits inside the Office of the CAIO and puts you at the center of how Labcorp is building, testing, and deploying agentic AI systems across the enterprise. You will work alongside senior engineers and data scientists on real agent development, contributing to projects that use frameworks like LangChain, LangGraph, CrewAI, and AutoGen, building on cloud platforms like AWS Bedrock, SageMaker, and AWS AI Deep Learning Containers (AI DLC), and working with frontier foundation models from OpenAI, Anthropic, Meta, and Mistral.
You will also get hands-on exposure to one of the hardest problems in enterprise AI: making agents safe. That means contributing to red teaming exercises, helping build guardrails and human-in-the-loop controls, learning how defense-in-depth architectures work, and understanding how Labcorp evaluates AI startups and emerging technology partners to bring the best capabilities into the enterprise safely. This is not a research exercise. You will contribute to agents that run in production, and you will help make sure they do not break things when they get there.
Agentic AI is the most important shift in enterprise software since the cloud. The companies that figure out how to deploy autonomous AI systems safely, at scale, inside regulated industries will define the next decade. This co-op puts you inside that work at a company where it actually matters: a Fortune 500 life sciences company that touches nearly half the U.S. population every year. You will not be building demos. You will be contributing to real agents that automate real workflows, with real guardrails, in a real production environment.
About the Co-op Program As a Labcorp Co-op, you’ll be immersed in hands-on work that complements your academic background. In addition to your project work, you’ll gain valuable exposure to Labcorp’s global business through:
- How a Fortune 500 life sciences company architects and deploys agentic AI systems at enterprise scale using the latest frameworks and cloud infrastructure
- How AI agents are designed to automate real business workflows with tool-calling, function-calling, and multi-step orchestration patterns
- How AI red teaming works in practice: adversarial testing, prompt injection, jailbreak resistance, and how vulnerabilities are identified and mitigated before production deployment
- How defense-in-depth architectures enforce safe agent behavior through guardrails, observability, human-in-the-loop controls, and red team oversight
- How frontier foundation models are benchmarked, evaluated, and selected for enterprise agentic use cases under real-world constraints (accuracy, cost, latency, safety)
- How enterprise AI governance works in a regulated healthcare industry, including model onboarding, agent risk assessments, and responsible AI compliance
- How Labcorp evaluates AI startups, emerging agentic frameworks, and frontier model providers to make build versus buy decisions
Co-op Details:
- Duration: Spring 2027 (with option for back-to-back Spring and Summer 2027)
- Dates of Internship: January 2027-May 2027
- Compensation: Paid Co-op
- Eligibility: Preferred candidates are Sophomore, Junior standing or Graduate student who are currently enrolled in a relevant degree program; however, all current students pursuing related studies are encouraged to apply
- Reports to: Executive Director, AI Science and Strategy
- This position is not eligible for visa sponsorship now or in the future.
Benefits: Employees regularly scheduled to work 20 or more hours per week are eligible for comprehensive benefits including: Medical, Dental, Vision, Life, STD/LTD, 401(k), Paid Time Off (PTO) or Flexible Time Off (FTO), Tuition Reimbursement and Employee Stock Purchase Plan. Employees regularly scheduled to work less than 20 hours, Casual, Intern, and Temporary employees are only eligible to participate in the 401(k) Plan. Employees who are regularly scheduled to work a 7 on/7 off schedule are eligible to receive all the foregoing benefits except PTO or FTO. For more detailed information, please click here.
Labcorp is proud to be an Equal Opportunity Employer:
Labcorp strives for inclusion and belonging in the workforce and does not tolerate harassment or discrimination of any kind. We make employment decisions based on the needs of our business and the qualifications and merit of the individual. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), family or parental status, marital, civil union or domestic partnership status, sexual orientation, gender identity, gender expression, personal appearance, age, veteran status, disability, genetic information, or any other legally protected characteristic. Additionally, all qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law.
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