About the role
Mirage is an AI-native video platform that intelligently orchestrates production and editing through natural language. Our models leverage contextual awareness to execute the same creative decisions a professional editor would — dramatically improving productivity for experienced teams, while making video creation accessible to anyone. We’re an interdisciplinary team addressing some of the most difficult technical and creative challenges in generative media. As an early member of our team, you’ll tackle foundational problems that remain largely unsolved across the industry, driving an outsized impact on the future of creative expression. More
about us Product (Captions by Mirage) Research (Seeing Voices, technical-white-paper) Updates (Mirage on X / twitter) TechCrunch , Forbes AI 50 , Fast Company (press) Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst , Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square)
About
the role This role focuses on designing and building agentic systems that power creative workflows for short-form video. You'll help shape how AI agents reduce friction, accelerate learning, and unlock new creative possibilities for our users — building agents that can take creative actions on a user's behalf — while experimenting with emerging models and techniques to bring these experiences to life in production. Software Engineers on the agents team work across product, machine-learning, and systems engineering — owning meaningful problems end-to-end and helping define how our agents are built and deployed across the product.
Responsibilities Build and ship end-to-end agentic systems that meaningfully improve creative workflows, balancing quality, performance, and reliability Design agent architectures — how agents gather context, plan, select tools, and execute creative tasks reliably at scale Integrate state-of-the-art models, combining internal research and external capabilities to power new agent experiences Measure and improve agent quality in production, using experimentation, evaluation frameworks, and real-world feedback to guide iteration What Makes You a Great Fit 5+ years of professional industry experience A track record of designing and developing ML systems or agentic pipelines in production Deep experience with context engineering: RAG systems, token optimization, context management at scale Experience building evaluation systems and agentic infrastructure (context gathering, tool selection, multi-step planning) Exceptional problem solving fundamentals and ability to learn quickly in a rapidly evolving space Able to operate effectively in an extremely fast-paced environment and scope and deliver projects end-to-end Even better if... You have worked with multi-agent architectures You have experience fine-tuning LLMs for specific use cases You have a pulse on where generative media and agentic AI technology is going You are grounded, collaborative, and willing to do whatever it takes to help