Flagship Pioneering: AI Automation Engineering Co-Op
About The Position
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
Benefits
- 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.
- healthcare coverage
- annual incentive program
- retirement benefits
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What This Job Offers
Job Type
Full-time
Career Level
Intern
