What are the responsibilities and job description for the AI Integration Engineer position at wellsfargo?
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)