Backend Engineer, AI-Powered Matchmaking (SF In-Person)

Known; San Francisco (CA); In loco; USD 200.000 - 350.000; Tempo pieno

Descrizione del lavoro

Known is seeking exceptional backend engineers to build the infrastructure that powers its core product, from real-time conversational AI to intelligent matchmaking.

This is a unique opportunity to contribute to the technical foundation for an AI-native consumer product, working across distributed systems, data infrastructure, and AI integrations to solve complex engineering problems at scale.

Competenze

• 4–6 years of backend experience in production systems.
• Proficiency in at least one backend language (Python/Go/TypeScript/Java).
• Experience designing APIs, distributed systems, and scalable architectures.
• Experience with relational databases, caching, asynchronous processing.
• Experience with cloud infrastructure (Docker, Kubernetes, AWS/GCP).
• Strong product intuition and ownership mindset.
• Interest in AI-powered matchmaking and scaling vision.

Mansioni

• Designing and scaling the backend services, APIs, and infrastructure that power Known's core consumer experience.
• Building real-time systems that support conversational AI, voice interactions, and agentic workflows.
• Architecting data pipelines and storage systems to support matchmaking, personalization, and machine learning.
• Developing reliable, low-latency services that connect our AI agents to real-world actions and third-party integrations.
• Improving the performance, reliability, security, and scalability of our systems as we grow to millions of users.
• Own systems end-to-end, from architecture and implementation to deployment, monitoring, and scaling.

Conoscenze

Python

Go

TypeScript

Java

APIs design

Distributed systems

Strumenti

Docker

Kubernetes

AWS

GCP

Descrizione del lavoro

Known is seeking exceptional backend engineers to build the infrastructure that powers its core product, from real-time conversational AI to intelligent matchmaking.

This is a unique opportunity to contribute to the technical foundation for an AI-native consumer product, working across distributed systems, data infrastructure, and AI integrations to solve complex engineering problems at scale.