Generative AI Intern

About CustomerInsights.AI, Inc (CIAI)
We are experts in Life Sciences Commercial Operations, and Technologists who are passionate about leveraging cutting-edge technologies including ML/AI to deliver on this vision. 
We believe that true value of AI will be realized by Pharmaceutical & Biotechnology companies when AI becomes part of one's everyday plumbing and not a one of event at the individual or project level.

Do you thrive on working on the cutting edge?

• Working with innovators in the early stages of ideas, products, or platforms?
• Do you crave new challenges and solving hard customer problems using the latest technology?
• Do you want to become part of a high-energy team and work very closely with the founding leadership team where you will play a key role in building a successful company that already has great traction?
• Are you an AI-native builder who already lives in these tools using AI to move faster and ship more than a traditional engineer, while knowing exactly where it falls short?

About the Role
CIAI is looking for a Generative AI & Agentic Systems Intern to join our AI engineering team, working at the intersection of frontier AI and real-world problems. This is not a passive learning role from week one you'll be building, shipping, and iterating on AI systems that go into production. We move fast, and we expect you as well.

You’ll work directly with large language models, multi-agent frameworks, and production-ready AI pipelines. In partnership with data scientists, product managers, and domain experts, you’ll help design systems that can reason, plan, and act autonomously. We’re looking for AI-native builders who use these tools fluently to move faster and deliver more than a traditional engineer, while recognizing their limitations and applying strong judgment.

What You'll Build:

• Agentic AI workflows using frameworks like LangGraph, AutoGen, or custom tool-use architectures
• Advanced RAG (Retrieval-Augmented Generation) building pipelines and orchestrations
• Fine-tuned or prompt-engineered LLMs tailored to the business requirements
• Evaluation harnesses to benchmark LLM accuracy, hallucination rates, and task performance
• AI prototypes integrated into existing platforms and demonstrated to executive stakeholders
• Monitoring and observability dashboards for deployed AI models (LLM tracing, latency, drift)
• Responsible AI guardrails: bias detection, content safety filters, and explainability layers 

What we’re looking for:

Required

• Pursuing a Bachelor's or Master's/PhD in Computer Science, Data Science, AI/ML, Mathematics, or a related field
• Graduating between Summer 2026 - 2027
• GPA of 3.0 or higher
• Proficiency in Python - you write clean, maintainable, well-documented code and able to explain the code back to the peers
• AI-native work style - you use tools like Claude, Cursor, or Copilot daily to accelerate your work, and you can speak to how you use them well while keeping a sharp eye on quality, correctness, and what the AI gets wrong
• Working experience with LLM framework (LangChain , LangGraph)
• Familiarity with transformer architecture, attention mechanisms, and the fundamentals of modern LLMs
• Ability to commit 40 hours/week for 12 weeks during Summer 2026
• Must not require U.S. work sponsorship

Strongly Preferred: 

• Project experience building agentic systems- tools, memory, multi-step reasoning
• Hands-on RAG implementation: chunking strategies, embedding models, retrieval tuning
• Experience with model evaluation, hallucination mitigation, or prompt safety
• Familiarity with vector stores, semantic search, or knowledge graph integration
• Contributions to open-source AI projects or a public portfolio 
• Experience with tool/function calling, MCP, or building custom agent tooling
• Familiarity with LLM observability and tracing (LangSmith, Langfuse, or similar)

What will you gain

• Mentorship from senior AI engineers, Product managers, and Principals
• Deep exposure to real-world AI applications, working on live products rather than toy problems
• End-to-end experience shipping AI into production, not just notebooks
• Real startup experience entrepreneurial pace, real ownership, and a front-row seat to building a company alongside the founding team