Software Engineer - Product
Luma AI
Software Engineering, Product
San Francisco, CA, USA
USD 170k-290k / year
About Luma
- A leading multimodal AI research lab, having built one of the world’s strongest video generation models (Ray-3.14)
- Pushing beyond video toward the next generation of multimodal general intelligence models
- Operating at a scale few companies can match, with the compute and resources to support frontier research ($900M Series C)
- Focused on the creative domain, where multimodal systems can have immediate real-world impact
- Shipping tightly integrated products that turn research breakthroughs into tools creators actually use
Where You Come In
What You’ll Do
- Use AI coding agents to ship features and products at a pace that would have been impossible a few years ago
- Work directly with product, design, and engineering teams to turn ideas into working software
- Learn rapidly across multiple domains—frontend, backend, systems, product, design
- Own meaningful product outcomes end-to-end
- Ship fast, get feedback, iterate, and improve
- Build your judgment about architecture, security, UX, and trade-offs by doing
Minimum Qualifications
- Bachelor’s degree in Computer Science or equivalent practical experience
- Experience building and shipping software (internships and substantial personal projects qualify)
- Strong proficiency in at least one general-purpose programming language (e.g., Python, TypeScript, Go, Java)
- 3+ years of professional software engineering experience, or can provide evidence of exceptional ability demonstrated through at least one standout accomplishment, such as:
- Owning and delivering a non-trivial software system or feature
- A substantial personal project with real users or adoption
- Success in a competitive programming contest, hackathon, or technical competition
- A significant open-source contribution or widely used library
What We Look For
- A demonstrated pattern of building software and shipping real work
- Evidence of learning new tools, patterns, or domains by building real things
- Experience using AI coding tools to build or ship non-trivial functionality
- Strong programming fundamentals (data structures, algorithms, systems thinking)
- Examples of ownership—identifying problems, taking initiative, and seeing work through
Why This Role Exists
- How quickly research becomes product
- How fast we can iterate
- How the next generation of engineers grows inside an AI-native company