Lead Backend Architect – Node.js, Cloud & AI

Acestack; Phoenix (AZ); On-site; USD 180,000 - 240,000; Full time

Job summary

Acestack is seeking a Lead Backend Architect with 10+ years of enterprise backend design experience to shape scalable cloud-native platforms in Phoenix. You will lead architecture, mentor teams, and drive AI integrations across services using Node.js, TypeScript, and modern cloud-native tools.

Applicants should have deep knowledge of AWS/GCP, Kubernetes, Docker, and CI/CD, plus experience with LLM integration, retrieval-augmented generation pipelines, and AI governance.

Qualifications

• 10+ years of experience in designing and building enterprise-scale backend systems.
• Strong hands-on expertise in Node.js, JavaScript, and TypeScript (must-have).
• Experience with AWS and/or GCP, Kubernetes, Docker, and CI/CD pipelines.

Responsibilities

• Lead the architecture, design, and implementation of scalable cloud-native backend platforms.
• Design and develop high-performance microservices and APIs using Node.js/TypeScript on AWS/GCP.
• Define architecture standards for distributed systems and event-driven solutions.

Skills

Architectural leadership

Mentoring

Stakeholder management

Technical guidance

Backend design

Tools

Node.js

JavaScript

TypeScript

Python

Go

AWS

GCP

Kubernetes

Docker

REST

gRPC

Kafka

LangGraph

LangChain

LlamaIndex

CrewAI

Semantic Kernel

PyTorch

Hugging Face

Job description

Job Title

Lead Backend Architect Node.js, Cloud & AI

Location

Phoenix, Az

Full Time

Job Description

Role

Lead Backend Architect Node.js, Cloud & AI

Experience Required

10+ Years

Must Have Technical/Functional Skills

12+ 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 integrating 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.