Job Title: Fullstack Developer
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.
Required Background
• 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.
Nice to Have
• 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.