AI Integration Engineer

Title: AI Integration Engineer

Location: Charlotte, NC

Duration: 103 W, 5 D

Work Engagement: W2

Work Schedule: Hybrid 3 days in office/2 days remote

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Software Engineering. Review and analyze complex multi-faceted, larger scale or longer-term Software Engineering challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Responsibilities:

• Contribute to AI‑first initiatives by integrating AI models, agents, and services into existing and new applications.

• Support projects centered on practical AI use cases, including automation, decision intelligence, and intelligent user experiences.

• Build and integrate AI agents that interact with internal systems, data sources, and business workflows.

• Partner with product, engineering, and platform teams as AI capabilities are scaled across the organization.

• Participate in the transfer and modernization of existing technology spaces as they move toward AI‑enabled solutions.

Key Requirements:

• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

• GenAI expertise

• Strong Java/Python programming experience for GenAI workflows, experimentation, and integration.

• practical experience building and deploying Applications powered by:

• Large Language Models (LLMs)

• Retrieval-Augmented Generation (RAG) pipelines

• Embeddings and vector databases

• Model Context Protocol (MCP) integrations and tool creation

• Agent frameworks and agent orchestration patterns

Desired Qualifications:

Java & Backend Engineering

Core Java, J2EE, Design Patterns

Spring Boot, Spring Security, Hibernate

API & Microservices

RESTful API development

Microservices architecture

Containerization (Docker/Kubernetes)

Testing & Build Automation

Unit Testing: JUnit, PowerMock

BDD experience

CI/CD using Maven, Gradle, Jenkins, HyperExecute.

Databases

MongoDB (NoSQL)

Oracle / MS SQL (RDBMS)