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Job Type: Full-time
Location: Remote (Must overlap PST timezone at least 6-8 hours)
Job Summary
This is a high-ownership fullstack role. You’ll own core product surfaces end-to-end — spanning architecture, backend systems, frontend execution, and production reliability. This is not a feature-factory role. You’re expected to make real architectural calls, raise the engineering bar, and move fast through ambiguity.
What You’ll Own
- Design and own end-to-end fullstack systems powering core product workflows.
- Architect and build clean, scalable backend services and APIs with strong contracts and clear ownership.
- Develop high-quality, performant frontend interfaces that directly ship to users.
- Own data modeling and database performance — schema design, query optimization, and long-term maintainability.
- Partner closely with product and design to translate ambiguous requirements into shipped systems.
- Set and uphold engineering quality standards through reviews, testing, and technical leadership.
- Debug and resolve production issues with urgency; improve reliability, observability, and failure modes.
- Make pragmatic tradeoffs between speed and correctness in a fast-moving AI-lab environment.
- Professional experience building and owning production fullstack systems.
- Strong TypeScript experience across frontend and backend.
- Solid backend expertise with Node.js (NestJS strongly preferred).
- Frontend experience building real products with React.
- Strong command of PostgreSQL and relational data modeling.
- Experience designing and maintaining RESTful APIs used at scale.
- Working knowledge of AWS or comparable cloud platforms.
- Experience with microservices and/or serverless architectures.
- Familiarity with Redis, queues, background workers, or async job systems.
- Strong systems thinking, ownership mindset, and attention to detail.
- Experience with CI/CD, infrastructure as code, or DevOps-leaning workflows.
- Background building cloud-native, production-grade systems from scratch.
- Exposure to AI-adjacent, data-heavy, or ML-powered products.
- Prior experience in high-velocity startup or lab-style environments where scope is fluid and impact is high.
Key Skills
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