Intern - Product + Engineering, AI Agents & Automation
About The Position
Help shape how AI transforms the way we build, ship, and scale products. As an intern, you’ll prototype intelligent systems that streamline workflows, accelerate decision-making, and unlock new efficiencies across product and engineering teams. About Hearst Magazines (Why Us?) Hearst Magazines is one of the world’s largest publishers of monthly magazines, with more than 30 brands in the U.S. and nearly 300 editions around the world. Our portfolio of more than 30 iconic brands—including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper’s BAZAAR, Men’s Health, Oprah Daily, and Women’s Health—connects with audiences across every platform, from print to digital to social and beyond. We inform, inspire, and entertain millions of readers globally.
Requirements
- Strong interest in AI/ML, automation, and building intelligent systems
- Comfortable writing code and building prototypes (e.g., Python, JavaScript, or similar)
- Familiarity with APIs, data workflows, or system integrations
- Ability to think in systems and break down complex problems into actionable steps
- Strong analytical and problem-solving skills with attention to detail
- Effective communicator who can collaborate with both technical and non-technical stakeholders
- Curious, proactive, and eager to experiment while focusing on real-world impact
- Based in New York City with the ability to work in-office 4 days per week
Nice To Haves
- Exposure to LLMs, agent frameworks, or automation tools is a plus
Responsibilities
- Partner with product and engineering leaders to identify high-impact workflows where AI agents can improve speed, quality, and efficiency
- Design and build agentic AI prototypes that can plan multi-step tasks, use tools/APIs, and operate with human oversight
- Translate real team needs into practical, production-minded solutions—not just exploratory demos
- Integrate prototypes with existing systems, tools, and data sources where possible
- Define success metrics and evaluate performance, reliability, and impact of AI-driven solutions
- Develop lightweight evaluation frameworks to assess outputs and guide iteration
- Document learnings and provide clear recommendations on what should be productionized
- Iterate quickly based on stakeholder feedback, balancing speed with thoughtful engineering tradeoffs
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What This Job Offers
Career Level
Intern
Education Level
No Education Listed
Number of Employees
501-1,000 employees
