Fullstack Software Engineer, Gen AI Systems

🕒 September 2

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

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Logo of Ayrin Digital

Ayrin Digital

11 - 50 employees

Founded 2025

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

Ayrin Digital is an AI-native software firm that helps businesses transform by building practical, accountable AI-first systems they own and govern. They position themselves as architects and builders who simplify data, replace fragile third-party SaaS dependencies, and deliver measurable, stakeholder-aligned outcomes—claiming fast ROI and scalable architectures that grow from a few users to millions. Their messaging emphasizes transparency (no black-box AI), accountability tied to business metrics, and delivering production-ready AI solutions for enterprise needs.

📋 Description

• Own features end-to-end from UI (React/Next.js) through API design (Node.js/NestJS) to cloud deployment • Partner with Product Owners and Subject Matter Experts to translate requirements into shipped solutions • Contribute product ideas that improve usability, performance, and business impact • Design and build multi-agentic systems where autonomous AI agents collaborate to solve complex, real-world tasks • Architect and implement RAG pipelines using vector databases and LLM orchestration frameworks • Take AI-powered features from prototype to production, owning model serving, latency optimization, cost management, and system reliability • Use AI SDK, LangGraph/LangChain, CrewAI, or equivalent tools to build and orchestrate AI workflows • Design, deploy, and manage scalable systems on AWS, GCP, or Azure • Apply cloud-agnostic thinking and understand core concepts regardless of provider

🎯 Requirements

• 3-5+ years of professional experience building production applications with React/Next.js, Node.js/NestJS, and PostgreSQL • Hands-on experience with at least one of: AI SDK (Vercel), LangGraph/LangChain, or CrewAI • Proven track record designing, orchestrating, and deploying multi-agent AI systems in production • Working experience with vector databases (Pinecone, Weaviate, pgvector, or similar) and RAG pipeline design • Strong understanding of AI deployment and system design: model serving, latency optimization, cost management, and production reliability • Experience with prompt engineering, model selection, and evaluation • Solid understanding of cloud concepts and services across AWS, GCP, or Azure • Experience deploying and managing production workloads in at least one major cloud platform

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