Jobs at Trinity Life Sciences

Supports Trinity’s Client Tech team in configuring and deploying customized technology solutions for life sciences clients. The intern identifies manual delivery processes, designs and implements AI-powered automation, supports engineering, data, DevOps, and testing workstreams, tracks efficiency gains, and documents best practices. The role includes mentorship, collaboration with technical stakeholders, and hands-on experience during a nine-week hybrid summer internship.

Supports product strategy by researching user needs, translating business requirements into product specifications, assisting with roadmap and sprint planning, tracking product and AI experience metrics, prototyping AI-enabled workflows, and supporting user training. Collaborates with product managers, engineers, data scientists, designers, and stakeholders in a hybrid nine-week internship focused on life sciences applications and emerging Generative AI and agentic AI technologies.

Supports the development, testing, and evaluation of AI, machine learning, generative AI, and analytics solutions for pharmaceutical and life sciences clients. Conducts research, validates models with real-world data, develops proof-of-concepts, and assists with model refinements. Prepares technical reports, presentations, proposals, and documentation while collaborating with data scientists, consultants, and engineers. Participates in training and mentorship during a nine-week hybrid summer internship.

Supports the Product Engineering team by researching and implementing generative AI models, building agentic workflows, evaluating and testing AI agents with real-world data, and collaborating on product enhancements. The intern also prepares technical documentation and presentations while receiving training and mentorship during a nine-week hybrid program.

Provides Tier I–III desktop and service desk support, escalates complex end-user issues, administers Microsoft 365 and endpoint environments, and manages IT assets and procurement. The role analyzes tickets, monitors SLAs and backlogs, produces reports, identifies trends, improves service operations, maintains documentation, and mentors junior staff. Responsibilities include troubleshooting hardware, software, peripherals, mobile devices, printers, security tools, Active Directory, and conferencing systems while supporting users in the New York EST region.

Owns end-to-end architecture and delivery of data products, including schemas, entity resolution, provenance, schema evolution, and normalization pipelines. Leads conversion of unstructured and semi-structured sources into enterprise-quality datasets using deterministic parsing, LLM-assisted extraction, inference, and human review. Partners with domain experts, data scientists, and AI engineers while applying strong SQL, Python, distributed processing, testing, observability, and CI/CD practices.

Build and deploy generative AI solutions for biopharma and life sciences clients, including Copilots, RAG pipelines, agentic workflows, and data integrations. Own projects from discovery through production, rapidly prototype and iterate with clients, and improve reusable AI components. Mentor and guide a small team of AI engineers through pairing, code reviews, onboarding, and technical coaching. Translate ambiguous client needs into production-quality systems while contributing to product development and knowledge-sharing.

Lead design and delivery of cloud-native, AI-first full‑stack applications. Architect scalable serverless and containerized services, implement pixel‑perfect UIs, build Django/GraphQL APIs, integrate LLMs and multi‑modal AI, enforce testing/CI/CD, observability, security, and mentor engineering teams while collaborating across product, design, and data.

Embed with biopharma clients to rapidly prototype and deploy GenAI solutions (RAG, LLMs, agentic workflows). Own end-to-end delivery from whiteboard to production, iterate with stakeholders, and feed learnings back into product.