GenAI Engineer - Data Analytics & Production AI

Infosys Limited; Princeton (NJ); On-site; USD 76,000 - 99,000; Full time

Benefits offered by this job

Disability insurance

Health and dependent care accounts

Insurance options (accident, critical-

401(k) plan

Job summary

Infosys Limited seeks a Technology Consultant 2 in Princeton, NJ, to drive Generative AI initiatives for data analytics within the Financial Services unit. You will document requirements, guide design decisions, and contribute to coding and production deployment of AI-enabled solutions.

The role emphasizes end-to-end SDLC involvement, collaboration with cross-functional teams, and ensuring system reliability through testing, reviews, and knowledge transfer.

Qualifications

• Bachelor’s degree or foreign equivalent required.
• Will consider three years of progressive experience in lieu of every year of education.
• Willingness to relocate and travel to work/project locations.

Responsibilities

• Document assigned parts of business requirements in line with guidance.
• Facilitate design discussions and document design decisions for the technical team.
• Participate in coding and integrate new features while maintaining stability.
• Conduct code reviews and maintain code repositories.
• Implement test strategies, analyze results, and coordinate bug fixes.
• Develop user training programs, documentation, and support frameworks.
• Resolve production issues and recommend preventive strategies to improve reliability.
• Maintain detailed records of code and testing to enrich the knowledge base.

Skills

Generative AI Engineering

Python

Gen AI Data Analytics

Education

Bachelor’s degree

Job description

Infosys Limited seeks a Technology Consultant 2 in Princeton, NJ, to drive Generative AI initiatives for data analytics within the Financial Services unit. You will document requirements, guide design decisions, and contribute to coding and production deployment of AI-enabled solutions.

The role emphasizes end-to-end SDLC involvement, collaboration with cross-functional teams, and ensuring system reliability through testing, reviews, and knowledge transfer.