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Mirage is an AI video company building multimodal agents and generative video models that make creative collaboration with AI dramatically easier. The company offers Captions, a creative workspace for video generation and editing, and Tesseract, a professional video engine for AI agents.
You will design and build end-to-end agentic systems that power creative workflows for short-form video. This role spans product, machine learning, and systems engineering, with ownership of meaningful problems from conception through production deployment. You'll help define how agents are architected, built, and scaled across the product.
Key responsibilities include:
- Building and shipping agentic systems that improve creative workflows while balancing quality, performance, and reliability
- Designing agent architectures covering context gathering, planning, tool selection, and reliable execution at scale
- Integrating state-of-the-art models, combining internal research and external capabilities
- Measuring and improving agent quality in production through experimentation, evaluation frameworks, and real-world feedback
- Operating end-to-end on projects in a fast-paced startup environment
The company is backed by top-tier investors including Sequoia Capital, Andreessen Horowitz, Kleiner Perkins, and Index Ventures. Most roles require in-person presence at the NYC HQ in Union Square.
REQUIREMENTS:
- 5+ years of professional industry experience
- 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
- Ability to operate effectively in an extremely fast-paced environment and scope/deliver projects end-to-end
PREFERRED:
- Experience with multi-agent architectures
- Experience fine-tuning LLMs for specific use cases
- Understanding of where generative media and agentic AI technology is heading
- Grounded, collaborative approach and willingness to do whatever it takes to help the team win
- Background as a startup founder or early engineer at a startup
