Full-Stack AI Engineer: GenAI, Cloud & REST APIs

U.S. Bank; Irving (TX); On-site; USD 93,000 - 109,000; Full time

Benefits offered by this job

Healthcare

401(k)

Paid vacation

Sick leave

Job summary

U.S. Bank is seeking a software engineer to design, develop, test, and maintain modern applications using Java, Spring Boot, React, and TypeScript, with REST APIs and cloud-native microservices.

The role emphasizes building AI-powered capabilities (LLMs, RAG, AI agents) and collaborating with cross-functional teams to translate business requirements into scalable solutions, while adhering to secure coding and DevOps practices.

Qualifications

• Bachelor’s degree, or equivalent work experience.
• Experience developing Java/Spring Boot/React/TypeScript applications.
• Knowledge of SQL/NoSQL databases and cloud platforms (Azure/AWS/GCP).
• Familiarity with cloud-native, microservices, and DevOps practices.
• Exposure to Generative AI tech (LLMs, RAG, AI agents).

Responsibilities

• Design, develop, test, and maintain modern software applications using Java, Spring Boot, React, and TypeScript.
• Build and integrate AI-powered capabilities including LLMs, RAG, and AI agents into business solutions.
• Develop and support REST APIs, microservices, and cloud-native apps with best practices.
• Collaborate with product owners, architects, and cross-functional teams to translate requirements.
• Participate in all SDLC phases including deployment and production support.
• Contribute to AI experiments and production implementations delivering business value.

Skills

Java

Spring Boot

React

TypeScript

RESTful APIs

Cloud platforms

Generative AI

Git/GitHub

CI/CD

Kubernetes

Education

Bachelor’s degree or equivalent

Tools

Git

GitHub Copilot

CI/CD pipelines

Automated testing

Docker

Kubernetes

Job description

U.S. Bank is seeking a software engineer to design, develop, test, and maintain modern applications using Java, Spring Boot, React, and TypeScript, with REST APIs and cloud-native microservices.

The role emphasizes building AI-powered capabilities (LLMs, RAG, AI agents) and collaborating with cross-functional teams to translate business requirements into scalable solutions, while adhering to secure coding and DevOps practices.