GenAI-Driven Full-Stack & Cloud Engineer

Machine Learning Technologies, LLC; Atlanta (GA); On-site; USD 110,000 - 170,000; Full time

Job summary

Machine Learning Technologies, LLC is seeking a Java Full Stack Engineer to design and deliver scalable applications in a cloud-native environment.

Responsibilities include collaborating with cross-functional teams, conducting code reviews, and enabling GenAI-assisted development to boost productivity and platform efficiency.

Experience with AWS, CI/CD, and modern front-end frameworks is preferred.

Qualifications

• Proficient in J2EE, Spring/Hibernate, and modern front-end frameworks.
• Experience building cloud-native architectures and CI/CD pipelines.
• Experience with GenAI tools to improve developer productivity.

Responsibilities

• Develop and maintain high-quality, scalable software solutions.
• Design and develop applications aligned with business and technical requirements.
• Participate in code reviews and follow engineering best practices.
• Create and maintain technical documentation, design specifications, requirements, and test plans.
• Support production systems, incident management, root-cause analysis, and problem resolution.
• Evaluate emerging technologies and participate in PoC initiatives.
• Contribute to technology roadmaps and modernization initiatives.
• Support application security, scalability, and operational resilience.
• Work collaboratively with engineering and business teams.
• May lead smaller initiatives or contribute as a specialized individual contributor.

Tools

J2EE

Spring/Hibernate

Angular/React

REST/SOAP APIs

Cloud-native architecture

AWS

CI/CD

Jenkins

Maven/Gradle

Chef

Sonar

GenAI tools

Job description

Machine Learning Technologies, LLC is seeking a Java Full Stack Engineer to design and deliver scalable applications in a cloud-native environment.

Responsibilities include collaborating with cross-functional teams, conducting code reviews, and enabling GenAI-assisted development to boost productivity and platform efficiency.

Experience with AWS, CI/CD, and modern front-end frameworks is preferred.