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Fullstack Engineer with AI

Iresh Technologies LLCUnited States🇺🇸United StatesPosted 25 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
United States
Posted
2 days ago
MicroservicesAWSAzureDatabricksGoogle CloudStakeholder Management

Job Description

Core skills needed                                                                                                                                     

  • 12+ years of full-stack engineering experience with a demonstrated ability to design, build, and scale production-grade applications.
  • 10+ years of experience delivering customer-facing technology solutions in consulting, product engineering, or enterprise environments.                                                                                                                                                         
  • Proven track record of leading end-to-end solution delivery, from architecture and development through deployment and operational support.                                                                                                                                                 
  • Hands-on experience building scalable data pipelines, APIs, microservices, and modern web applications.                                                                                                                                                   
  • Experience designing and implementing AI-powered applications using Large Language Models (LLMs), including integration with platforms such as OpenAI, Anthropic, and Google Gemini.                                                                               
  • Strong understanding of Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, model evaluation, and enterprise AI application patterns.                                                                                                                                                      
  • Proficiency with AI-assisted software development tools, including GitHub Copilot and other developer productivity platforms.                                                                                                                                               
  • Hands-on experience developing and deploying cloud-native solutions on AWS, Azure, or Google Cloud Platform.                                                                                                                                                          
  • Experience implementing CI/CD pipelines, automated testing, infrastructure-as-code, and production deployment best practices.                                                                                                                                                     
  • Strong understanding of application security, observability, monitoring, and operational excellence in enterprise environments.                                                                                                                                                         
  • Databricks Data Engineer Professional certification preferred; hands-on Databricks experience is highly desirable.                                                                                                                                                          
  • Excellent communication, stakeholder management, and consulting skills, with the ability to translate business requirements into scalable technical solutions.       

 

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