Backend Architect Node.js, Cloud & AI

Role - Lead Backend Architect Node.js, Cloud & AI Location - NYC NY (onsite) Job Type- Full Time Employment

Job description Below 10+ years of experience in designing and building enterprise-scale , cloud-native backend systems and distributed architectures . Strong hands-on expertise in Node.js, JavaScript, and TypeScript (must-have), with working knowledge of Python and Go. Extensive experience developing microservices, REST/gRPC APIs, event-driven architectures, and scalable backend platforms. Strong expertise in AWS and/or GCP, Kubernetes, Docker, cloud-native architecture , and CI/CD pipelines. Experience with distributed messaging and streaming technologies such as Kafka, queues, and asynchronous processing. Proven experience designing highly available, secure, scalable, and resilient backend systems. Strong understanding of databases (SQL/NoSQL), caching, observability, logging, and performance optimization. Mandatory experience integrating Large Language Models (LLMs) into enterprise applications and backend platforms. Hands-on experience with Agentic AI frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or Semantic Kernel. Experience building Retrieval-Augmented Generation (RAG) pipelines, AI orchestration workflows, and LLM gateways. Working knowledge of PyTorch, Hugging Face ecosystem, embeddings, inference, and model evaluation. Strong understanding of AI governance, evaluation, safety, and responsible AI practices. Excellent architecture, technical leadership, stakeholder management, and mentoring skills.

Required Technologies Languages: Node.js, JavaScript, Typescript, Python, Go Cloud: AWS/GCP Containers: Kubernetes, Docker APIs: REST, gRPC Messaging: Kafka or equivalent AI Frameworks: LangGraph, LangChain, LlamaIndex, CrewAI, Semantic Kernel ML: Hugging Face, PyTorch DevOps: CI/CD, Terraform (preferred)

Roles & Responsibilities

Lead the architecture, design, and implementation of scalable cloud-native backend platforms for Lounge Services. Design and develop high- performance microservices and APIs using Node.js/TypeScript on AWS/GCP. Define architecture standards for distributed systems, event-driven solutions, messaging, and cloud-native applications. Drive the adoption of AI capabilities by integrati ng LLMs and Agentic AI into enterprise backend services. Design and implement reusable AI platform components including orchestration, RAG pipelines, model gateways, and AI observability. Provide technical leadership across engineering teams, driving architecture reviews, engineering best practices, and technology decisions. Collaborate with Product, Engineering, Security, and Enterprise Architecture teams to deliver scalable and secure solutions. Mentor engineering teams and influence technical direction across multiple initiatives. Evaluate emerging backend, cloud, and AI technologies and recommend enterprise adoption where appropriate. Ensure solutions meet enterprise standards for scalability, reliability, security, performance, and operational excellence.