VectorShift provides tooling to create custom AI workflows quickly. End-users can run and modify these pipelines using our no-code platform, and developers can ship complex production-grade AI chains directly to end-users using our API and SDK. In addition to expanding our core platform, we are working with several >$1bn revenue enterprises to pilot our solutions for specific high-impact use cases.

VectorShift is a No-Code Generative AI Platform.

As an Backend Engineer you will build new and work on existing VectorShift’s product lines (e.g., improving workflow run efficiency and scalability, integrate new developments in AI into our platform, manage our database infrastructure).

This will be a challenging and dynamic role, and you will be working at the forefront of distributed systems infrastructure and AI.

Along with building product lines, you can also expect to:

• Build integrations of the VectorShift platform with 3rd party applications
• Talk with customers to understanding core pain points and iterating with them on feature requests.
• Contribute to customer support, especially for the products you build!
• Stay up to date with the latest developments in AI to integrate new capabilities into our platform.

Responsibilities:

• Work directly with the founders to conceptualize and implement sub-products and features, end to end.
• Lead technical architecture decisions, ensuring the platform is scalable and maintainable.
• Drive forward performance optimization.
• Establish foundational technical practices that will guide future team members.

Requirements:

• Degree in a technical discipline, preferably computer science.
• Experience with Python/ FastAPI.
• Understanding of performance optimization best practices.
• Strong communication skills and ability to work in high paced environments.
• Excellent problem solving skills and proven ability to overcome challenges.

Nice to Have:

• Experience in early-stage startup environments.
• Experience with no/low-code platforms.
• Experience in AI, machine learning, and building RAG workflows.

Our frontend is built using React/NextJS. We run our backend using Python/FastAPI and use MongoDB/Redis for data storage.