Software Engineer, Agents

Mirage•New York, NY

1d•$175,000 - $275,000•Onsite

About The Position

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.

Requirements

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

Nice To Haves

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 the team win
You have been a startup founder or an early engineer at one

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