Flagship Pioneering: AI Automation Engineering Co-Op

United Kingdom·Cambridgemid

OtherEngineering Co

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Quick Summary

Overview

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.

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OtherEngineering Co

What We Offer

~4 min read

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.

✓Build alongside founders. You’ll work inside the same hypothesis-driven process Flagship uses to conceive and launch first-in-category companies.

✓This can be the start of a longer story. Strong co-ops are considered for future opportunities across Flagship and its portfolio companies, not just for this one role.

✓Work alongside people who left the safe path. Your colleagues are scientists, engineers, and operators who chose to build something new rather than join something already established.

✓Take on real ownership. You're contributing to ventures that are still being defined. Your work can shape real decisions, not just support them.

✓Be paid like the contributor you are. Compensation reflects the real work you take on.

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.

This role is for builders who are curious, resourceful, and eager to learn. You don’t need to know everything, but you should be excited to figure things out. You’re a strong fit if you:

Have looked at a manual process and thought, “This wouldn’t exist like this if it were built today”
Like to prototype quickly and learn by building
Have hands-on experience building with AI tools, models, or APIs, even in personal or school projects
Are starting to develop instincts for choosing the right tool for the job, not just using the one you know best
Ask questions about why something is designed a certain way, not just how to make it work
Care about whether something actually works reliably, not just in a demo
Are energized by new technology and lean into learning it
Can explain what you built and why to someone non-technical

Responsibilities

~1 min read

→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

Requirements

~1 min read

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

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