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) seeks an experienced AI Engineer to design and implement a scalable, enterprise-grade AI platform. You will create reusable AI components, LLM services, and modular workflows to be configured across multiple projects and clients.

The role covers building plug-and-play AI modules, developing REST APIs and microservices, and deploying secure, scalable solutions on cloud platforms with Docker and CI/CD pipelines.

Qualifications

• Experience with Generative AI, LLMs and AI application development.
• Experience with RAG, embeddings and vector stores.
• Knowledge of APIs, microservices and modular architectures.

Responsibilities

• Design reusable AI components, LLM services, AI agents and workflows.
• Build plug-and-play AI modules with Python, Generative AI, LLMs and prompt engineering.
• Develop REST APIs and microservices for enterprise integration.
• Ensure scalable, secure, configurable, versioned and maintainable solutions.
• Deploy production AI services on cloud platforms using Docker and CI/CD.

Skills

Generative AI & LLMs

RAG & embeddings

APIs & microservices

Cloud platforms (Azure/AWS/GCP)

Docker & CI/CD

AI security & governance

Tools

LangChain

LangGraph

LlamaIndex

Docker

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 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.