AI Engineer – Enterprise AI Platform

GBIT (Global Bridge InfoTech Inc); McKinney (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

GBIT (Global Bridge InfoTech Inc) is seeking an experienced AI Engineer to build a scalable, enterprise-grade AI platform with reusable, configurable components that can be deployed across multiple projects and clients.

You will design and implement LLM services, AI agents, and modular workflows, assemble plug-and-play AI modules, and deliver REST APIs and microservices running on cloud platforms. Collaboration with engineering teams is essential to enforce reusable architecture and standards.

Qualifications

• 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.

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 enterprise integration.
• Ensure scalability, security, configurability, versioning, monitoring, and maintainability.
• Deploy production-ready AI services on cloud platforms using Docker and CI/CD.
• Collaborate with engineering teams to establish reusable architecture and enterprise standards.

Skills

Generative AI

LLMs

AI applications

RAG

LangChain

LlamaIndex

Vector databases

APIs & microservices

Cloud platforms

Docker

CI/CD

AI security

Tools

LangGraph

Job description

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 they 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.