New Products & Strategies Summer Intern – Generative AI

Trinity Life Sciences•Barrington, RI

1d•$35•Hybrid

About The Position

We're committed to bringing passion and customer focus to the business. We are seeking a highly motivated and talented individual to join Trinity Life Sciences as a Generative AI Engineering Intern on our New Products & Strategies team. In this role, you will help design and build agentic GenAI applications and workflows that power our product offerings for clients in the pharmaceutical and life sciences industry. You will work closely with our engineering and product teams to integrate large language models into real-world systems, orchestrate tool-using agents, and ship practical features. Interns develop their skills through undergoing extensive formal and informal training, as well as receiving mentorship that encourages them to stretch their analytical skills. This is a 9-week internship program based out of Trinity’s headquarters in Waltham, MA – interns will be required to work in a hybrid work model, coming into the office about 2-3 days per week. The dates for the program run from June 15 to August 14, 2026.

Requirements

Candidates should be enrolled in a graduate or undergraduate program in computer science, engineering, mathematics, or related field.
Trinity is targeting current Juniors, or students in a Masters program with 1 year left in their studies.
Strong programming skills in TypeScript and JavaScript, with experience building backend services and APIs using Node.js
Comfortable working in a modern TypeScript ecosystem: package managers, linting/formatting, unit/integration testing, and basic build tooling.
Familiarity with AI coding assistants and agentic development tools such as GitHub Copilot, Claude Code, Cursor, or similar tools used to navigate, refactor, and extend real-world codebases.
Experience integrating external APIs (REST/JSON), handling authentication, and managing configuration via environment variables and secrets.
Understanding of core software engineering practices: Git-based workflows, code reviews, debugging, and writing maintainable, well-structured code in a team setting.
Interest in or experience with LLM-based applications (chatbots, assistants, copilots) and calling model APIs from TypeScript/Node.js.
Ability to work independently on well-scoped tasks, ask good questions, and communicate clearly with both technical and non-technical stakeholders.

Responsibilities

Support the design and development of AI-powered agents and agentic workflows for life sciences use cases, including research copilots, data analysis pipelines, and decision-support tools
Build and integrate LLM-based applications using modern frameworks (e.g., LangChain, LangGraph, or similar orchestration tools)
Experiment with prompting strategies, tool use, memory, and retrieval (RAG) to improve agent performance and reliability
Research emerging techniques in generative AI, including multi-agent systems, tool calling, and model optimization
Collaborate with engineers, data scientists, and domain experts to translate business and scientific requirements into AI-driven solutions