Flagship Pioneering: AI Automation Engineering Co-Op

Flagship Pioneering•Cambridge, MA

4d•Onsite

About The Position

This position is open exclusively to current Northeastern University Co-Op students. Work Period: January 2027 to June 2027. This is a full - time, 40 hours per week position with 5 days in office. Flagship Pioneering is a biotechnology company that invents and builds platform companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health and sustainability exponentially accelerate scientific progress in areas ranging from cancer detection and treatment to nature-positive agriculture. What sets Flagship apart is our ability to advance biotechnology by uniting life science innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet. Many of the companies Flagship has founded have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE’s “Change the World” list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company’s annual list of the World’s Most Innovative Companies. Welcome to Flagship Pioneering Co-Op Program for the cohort dreaming big and taking courageous leaps.You'll join fellow peers across our ecosystem of companies and learning firsthand how we build first-in-category companies. You’ll have access to enrichment sessions , a dedicated professional development track , and a mentor that help guide you toward your next step. By the end, you will carry on a meaningful project outcome , a genuine network , and a front-row view of how Flagship pioneer new ventures that change the world. This is a hands-on building role. You will work closely with cross-functional stakeholders to design, prototype, and deploy AI-powered solutions that improve how teams work. Projects range from low-code automations using platforms like Zapier, Vercel, and Workato to full-stack applications built with tools like Claude Code and VS Code, written in Python or JavaScript, and deployed on cloud infrastructure like AWS. You will take ownership of projects from start to finish: understanding a business process, exploring how to redesign it with AI, building a working solution, and iterating until it holds up in practice. We’re looking for someone who is curious about not just how to build, but how to build well. That means learning to evaluate which tools and approaches fit a given problem, thinking through a design before jumping into code, and being open to feedback on your approach along the way.

Requirements

Current graduate student in Computer Science, Information Systems, or a related field
Proficiency in at least one programming language (e.g., Python, JavaScript)
Basic understanding of APIs, webhooks, and how web services communicate
Comfort working with AI tools in a development or productivity context
Strong problem-solving skills and a willingness to learn new tools quickly

Nice To Haves

Experience with low-code or no-code automation platforms (e.g., Zapier, Make, Power Automate, Workato)
Experience building and deploying applications on cloud platforms (e.g., AWS, Azure, GCP)
Familiarity with version control (Git) and development environments like VS Code

Responsibilities

Build and deploy automations using low-code platforms (e.g., Zapier, Workato) and, where needed, custom code (e.g., Python, JavaScript) to automate business workflows
Integrate AI models via APIs into automation pipelines
Help deploy and maintain applications on cloud infrastructure (e.g., AWS)
Learn to evaluate different tools and approaches for new projects, considering tradeoffs like speed, complexity, and long-term maintainability
Test your own work thoroughly, with a focus on accuracy and edge cases, especially for data-sensitive workflows
Iterate on proof-of-concept solutions based on real-world performance and feedback from business stakeholders
Keep clear notes on how your solutions are built so others can understand, maintain, and extend them
Support AI tool pilots and help create training materials that make it easier for non-technical users to adopt AI-enabled workflows