AI Automation Co-op (Spring 2027)

Later is the world’s most intelligent influencer marketing company, built to give brands the confidence to create unforgettable campaigns. By combining real creator relationships, trusted intelligence, and expert guidance, Later removes fear and guesswork from one of marketing’s most visible investments. Built on a native, AI-powered platform and more than a decade of proprietary data—including billions of social interactions, impressions, and $2.4B+ in verified influencer-driven purchases—Later helps teams understand what will work before they launch. By combining trusted insight with expert guidance, Later removes guesswork from influencer marketing, enabling brands to choose the right creators, execute fully managed campaigns, and drive meaningful growth across awareness, engagement, and revenue. Trusted by leading enterprise brands including Nike, Wayfair, Unilever, and Southwest Airlines, Later bridges creativity and performance so campaigns don’t just look good—they deliver results. Learn more at later.com. About this position: We're looking for an AI Automation Co-op to embed with teams across Later and help replace manual, repetitive work with AI-powered tooling. This is a hands-on role at the intersection of building and learning: you'll contribute directly to automations that create real business impact across Operations, Finance, Marketing, Customer Success, and beyond while being supported and coached throughout. This role will begin in January 2027. You'll work closely with Later's AI Automation team and get direct exposure to how AI tools, APIs, and no-code platforms come together to solve real workflow problems across Later's three lines of business (Later Influence, Later Social, and Later Creator). If you're curious about applied AI, love tinkering with new tools, and want to leave a term with a portfolio of things you actually shipped, this is the role for you. What you'll be doing: Discovery & Problem Scoping • Shadow and interview non-technical stakeholders across Operations, Finance, Marketing, and Customer Success to understand their day-to-day workflows. • Help identify repetitive, manual tasks that are strong candidates for automation. • Contribute to translating fuzzy workflow problems into clear, scoped technical solutions with guidance from the team. Building & Shipping • Build working automations and internal tools using AI-native platforms, APIs, and no-code and low-code tools. • Ship v1 prototypes quickly so stakeholders can validate value before investment grows. • Wire together LLMs, agents, and prompt design patterns with existing systems to deliver real workflow outcomes. • Iterate on automations based on stakeholder feedback and real-world use. Documentation & Reliability • Write clear documentation so automations can run unattended and teammates can understand what was built. • Contribute to error handling and basic monitoring so automations recover gracefully. • Help maintain a library of reusable templates, prompt patterns, and integration examples. Enablement & Collaboration • Support working sessions and lightweight training that helps non-technical colleagues understand and use the automations you build. • Collaborate with engineers, operations teammates, and other stakeholders to deliver solutions that work in practice. • Share what you learn openly, contributing to Later's growing citizen-developer community. What success looks like: • By the end of your term, you have at least 2-3 automations in production with documented business impact (hours saved, error rates reduced, or cycle times shortened) across different teams. • Stakeholders can use and understand the automations you built without needing you to explain them every time, because you wrote documentation that actually works. • You've grown your fluency with AI-native tools, APIs, and no-code platforms and can talk clearly about the tradeoffs of different approaches. • You've contributed at least one reusable component, prompt template, or integration pattern to Later's shared automation library. • You leave the term having built real things that are still running, and with a clearer sense of where you want to take your career in applied AI and automation. What you bring: • Currently enrolled in a Computer Science, Software Engineering, Data Science, or related program, or equivalent practical experience. • Some experience building with code (Python, JavaScript, C# or similar) and comfort picking up new tools quickly. • Curiosity about AI and automation: you've experimented with LLMs, prompt design, or no-code tools and want to go deeper. • A bias toward action: you'd rather ship something imperfect and learn from it than wait for a perfect plan. • Strong written and verbal communication skills, you can explain a technical idea to someone who doesn't code. • Comfort with ambiguity: you can make progress on a loosely defined problem without needing every detail up front. • Familiarity with APIs, scripting, or automation tools (Zapier, Make, n8n, or similar) is a bonus. • Any experience with data: pulling it, cleaning it, and reasoning about what it means, is a plus. How you work: • Driven by Impact: You deliver results that matter—prioritizing high-value work, meeting deadlines, and adapting quickly while keeping outcomes clear. • Strategic & Customer-Centric: You anticipate risks and opportunities, connect decisions to long-term growth, and build trust through proactive insights. • Curious & Growth-Oriented: You seek knowledge, ask sharp questions, and apply learnings fast—challenging the status quo with a mindset of improvement. • Collaborative & Resilient: You thrive in change by staying resourceful, solution-focused, and positive—removing roadblocks, sharing insights, and keeping morale high. • Accountable & Honest: You own your work, hold yourself and others to a high bar, and use transparent feedback to drive growth. • Emotionally Inte