You'll ship real products to real users at Luma, working close to experienced technical leaders and using AI coding agents to build at a pace that wasn't possible a few years ago. This is a role for an engineer early in their arc who's already shipping at a high level.
You likely have senior-level impact but not yet the years of production scars - the large-scale failures and long-lived architectural bets. That's what you'll gain here, quickly. It's a build role, not a wait-for-tickets role. If you want gradual, tightly-scoped progression, this compresses that curve in a way that won't suit everyone.
What You'll Own- Use AI coding agents to ship features and products fast.
- Work directly with product, design, and engineering to turn ideas into working software.
- Learn rapidly across frontend, backend, systems, product, and design.
- Own meaningful product outcomes end to end.
- Ship, get feedback, iterate, and build judgment on architecture, security, UX, and trade-offs by doing.
First 90 DaysOne way the first 90 could unfold.
- Days 1-30 - Immerse & Diagnose: Get into the codebase and product, and ship your first real changes.
- Days 30-60 - Ship & Validate: Own a meaningful product outcome end to end with real users.
- Days 60-90 - Scale & Systemize: Take on larger surface area and sharpen your architectural judgment.
What You Bring- Experience building and shipping software (internships and substantial personal projects count).
- Strong proficiency in at least one general-purpose language (Python, TypeScript, Go, Java).
- 2+ years of professional software engineering, or clear evidence of exceptional ability: a non-trivial system you owned, a personal project with real users, a competition win, or a significant open-source contribution.
- Strong fundamentals in data structures, algorithms, and systems thinking.
- Experience using AI coding tools to ship non-trivial functionality.
- Bachelor's in Computer Science or equivalent practical experience.
Nice to Have- A demonstrated pattern of building and shipping real work.
- Evidence of learning new tools and domains by building real things.
- Examples of ownership: identifying problems, taking initiative, and seeing work through.
This role is defined by learning speed and output, not years of experience.
