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AI Engineer – Enterprise AI Platform

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Onsite

AI Engineer – Enterprise AI Platform

GBIT (Global Bridge InfoTech Inc)

AI Engineer – Enterprise AI Platform

Skills

Google Cloud PlatformDockerPythonMicroservicesAIAWSAzure

6 days ago

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Important information


Contract type:

Permanent

Location:

Irving, TX, USA

Work mode:

Onsite

Published on:

17 October 2026

What they need


We are looking for an experienced AI Engineer to build a scalable, enterprise-grade AI platform with reusable, modular, and configurable AI capabilities. The goal is to develop components once and enable teams to configure, integrate, and reuse them across multiple projects, clients, and applications, reducing development time, cost, and duplication.

Key Responsibilities:

  • Design and develop reusable AI components, LLM services, AI agents, and intelligent workflows.
  • Build plug-and-play AI modules using Python, Generative AI, LLMs, RAG, and prompt engineering.
  • Develop REST APIs and microservices for seamless integration with enterprise applications.
  • Ensure scalability, security, configurability, versioning, monitoring, and maintainability.
  • Deploy and optimize production-ready AI services on cloud platforms using Docker and CI/CD.
  • Collaborate with engineering teams to establish reusable architecture and enterprise development standards.

Required Skills:

  • Strong hands-on experience with Generative AI, LLMs, and AI application development.
  • Experience with RAG, embeddings, vector databases, and frameworks such as LangChain, LangGraph, or LlamaIndex.
  • Strong knowledge of APIs, microservices, modular architecture, and reusable components.
  • Experience with Azure/AWS/GCP, Docker, CI/CD, and production deployments.
  • Understanding of AI security, governance, monitoring, and performance optimization.

Preferred: Experience building enterprise AI platforms, reusable AI services, AI agents, or configurable SaaS solutions.

Ideal Candidate: A hands-on AI Engineer capable of transforming AI capabilities into secure, scalable, reusable components that can be easily configured and deployed across multiple business use cases.

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