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AI Data Engineer

ARSquare Tech LLCNew York, NY🇺🇸United StatesPosted 24 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
2 days ago
DockerAWSETLAzureGitGoogle CloudKubernetesLLMPython

Job Description

Required 9+ Years of experience

Required Qualifications

  • Strong experience in Python application development.
  • Strong background in data engineering, data analytics, BI, or data application development.
  • Experience with cloud platforms and Kubernetes-based application/pipeline deployment.
  • Strong hands-on experience building production-grade data pipelines.
  • Strong understanding of data architecture, data processing, ETL/ELT, and data integration.
  • Experience working with databases, data warehouses, and/or modern data platforms.
  • Experience building data-facing applications or applications that interact directly with data and analytics platforms.
  • Hands-on experience developing LLM-powered applications.
  • Understanding of AI agent/harness engineering patterns and LLM application architecture.
  • Experience working with APIs, databases, data platforms, and enterprise data sources.  
  • Cloud development experience with Kubernetes-based deployment.
  • Strong software engineering fundamentals including Git, testing, CI/CD, and production deployment.
  • Demonstrated ability to work independently and take ownership from requirements through delivery.
  • Strong analytical, troubleshooting, and communication skills.

Preferred Qualifications

  • Experience with agentic AI, LLM orchestration, RAG, or tool-using agents.
  • Experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.
  • Experience with vector databases and retrieval pipelines.
  • Experience integrating LLMs with enterprise data platforms.
  • Experience building dashboards, analytics applications, self-service data applications, or other data-centric user experiences.
  • Experience with AWS, Azure, or Google Cloud Platform.
  • Experience with Docker and Kubernetes.

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