Backend Engineer (Node.js)

TL;DR

Backend Engineer (Node.js): Building scalable backend systems and infrastructure for a consumer AI product with an accent on API design, real-time communication, and data architecture. Focus on architecting reliable, performant services to handle complex workflows like streaming LLM responses, payment processing, and real-time chat at scale.

Location: On-site in San Francisco

Company

hirify.global is a venture capital firm backing Known, a consumer AI product.

What you will do

• Design and build scalable backend services in Node.js/TypeScript, including RESTful APIs and data pipelines.
• Architect and optimize database systems using Postgres for schema design, query optimization, and data integrity.
• Implement real-time communication infrastructure using WebSockets and WebRTC for low latency and high reliability.
• Integrate and manage third-party services like OpenAI/Anthropic LLMs, payment platforms, and notification systems.
• Collaborate with AI/ML engineers to build APIs and data pipelines for model predictions and training data.
• Own infrastructure, deployment, and observability, including CI/CD pipelines, monitoring, and cloud cost optimization.

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 a deep understanding of async patterns and performance optimization.
• Expert-level knowledge of Postgres, comfortable with complex queries, transactions, and performance tuning.
• Experience designing and scaling RESTful APIs with attention to rate limiting, authentication, and caching.
• 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.

Culture & Benefits

• Opportunity to be the infrastructure architect of a consumer AI product from day one.
• Autonomy to make foundational technical decisions.
• Responsibility for ensuring the product can scale from thousands to millions of users.
• Chance to enable rapid product innovation.