Full Stack Software Engineer at Vendora (W23)
Vendora | New York, New York, United States | 2mo ago
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Original posting (closed) below
$70,000 – $160,000/yr| full-time | on-site | mid | 0+ years | visa sponsorship
skills: typescript, react.js, react native, node.js, next.js, express, tailwind, reactative, shadcn, mongodb, postgresql, supabase, aws, gcp, docker, kotlin, swift, c#, llm, rag, pytorch, machine learning, devops
We’re hiring a full stack software engineer to join our small, yet mighty team. We ship and maintain a ton of software. We do it with way less than the incumbents. That requires a builder culture, bias for action, and maniacal customer obsession.
You’ll cover a lot of ground. Imagine building APIs that sync hundreds of thousands of products across multiple platforms in seconds one day, designing a model that pinpoints exactly when a store needs to reorder merchandise another day, and integrating our software with multiple hardware vendors the next. If that excites you, we invite you to apply.
This role is in-person five days a week in our Williamsburg office.
Key Responsibilities:
- You’ll ship entire products end to end as well as building and maintaining features across mobile, web, and backend. No task too big or small.
- Be your own product manager and deal with ambiguity, understand what we are building for customers, why, and build to that vision.
- Talk to our users every chance you get. You’ll be frontline support and engage closely with customers on what they want and need
- Have high standards, drive engineering excellence, introduce new ideas, and solve problems
- Build a resilient, scalable foundation for growth. Design systems that last and document them well so others can build on your work.
Our Stack:
- Javascript (Typescript, React.js, React Native, Node.js, Next.js, Express)
- Tailwind/Nativewind, Shadcn
- MongoDB and PostgreSQL (Supabase)
- AWS, GCP, Docker
Nice-to-Have Experience:
- Native development (Kotlin, Swift, C#), especially developing for Windows
- LLM applications (using RAG, agent frameworks, etc.)
- Machine Learning, specifically pytorch and open source models
- DevOps (infrastructure as code, observability, monitoring, security)
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