Backend Engineer - Known

Architect and optimize database systems using Postgres — including schema design, query optimization, indexing strategies, and data integrity at scale.

Implement real-time communication infrastructure using WebSockets for chat and WebRTC for audio/video, ensuring low latency and high reliability.

Integrate and manage third-party services (OpenAI/Anthropic LLMs, Google/Apple Pay, reservation platforms, SMS/push notifications, CDNs) with robust error handling and monitoring.

Collaborate with AI/ML engineers to build APIs and data pipelines that serve model predictions, handle training data collection, and support experimentation workflows.

Own infrastructure, deployment, and observability — build CI/CD pipelines, implement monitoring and alerting, optimize cloud costs, and ensure system reliability as traffic scales.

Design for performance and scale — implement caching strategies, optimize API response times, and architect systems that can handle 10x growth without rewrites.

Requirements

4–6 years building production backend systems, ideally in consumer products, high-traffic applications, or startups.

Strong proficiency in TypeScript and Node.js with deep understanding of async patterns, performance optimization, and error handling.

Expert-level knowledge of Postgres — you’re comfortable with complex queries, transactions, indexing, connection pooling, and performance tuning.

Experience designing and scaling RESTful APIs with attention to rate limiting, authentication, caching, and versioning.

Hands-on experience with cloud platforms (AWS, GCP) including compute, storage, databases, and networking services.

Familiarity with containerization and orchestration (Docker, Kubernetes) and infrastructure-as-code tools.

Experience with WebSockets and WebRTC for real-time communication systems.

Strong understanding of observability and monitoring — logging, metrics, tracing, and alerting best practices.

You think about security, data privacy, and compliance as first-class concerns.

Example Projects

Build a high-throughput API layer that serves personalized match recommendations, user profiles, and compatibility scores with sub-100ms response times.

Design and implement a background job system for processing batch matching algorithms, sending notifications, and generating analytics reports.

Create WebSocket infrastructure for real-time messaging with presence indicators, typing notifications, and streaming LLM-powered conversation suggestions.

Architect WebRTC signaling and media server infrastructure to support voice/video chat between users and AI voice agents.

Build payment and reservation integration workflows with idempotency guarantees, webhook handling, and comprehensive error recovery.

Implement a robust caching layer (Redis) that reduces database load and improves API response times across the platform.

Design database schemas and migration strategies that support rapid product iteration while maintaining data consistency and performance.

Expand monitoring and observability infrastructure with distributed tracing, performance profiling, and automated alerting for system health.

Why This Role

This is a chance to be the infrastructure architect of a consumer AI product from day one — to build backend systems that are elegant, scalable, and enable rapid product innovation. You’ll have the autonomy to make foundational technical decisions and the responsibility to ensure Known can grow from thousands to millions of users without missing a beat.