Backend Architect , Cloud & AI

Role - Lead Backend Architect 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 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: 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 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.

Required Skills:

Intelligence