Gen AI Engineer: LLMs & Agentic Systems

Infosys; Hartford (CT); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k) plan

Paid holidays plus PTO

Disability insurance

Job summary

Infosys Topaz seeks a Technology Consultant 2 with strong Gen AI experience to design, develop, and deploy AI-enabled solutions. You will help elicit requirements, guide architecture discussions, and implement features in Python using LangGraph, LangChain, and modern ML tools.

You will participate in end-to-end SDLC, conduct code reviews, and improve system reliability. The role includes creating training materials and coordinating deployment with cross-functional teams in a dynamic environment.

Qualifications

• Experience in designing, developing, and deploying Gen AI applications using LLMs and agentic frameworks.
• 2-3 years in Gen AI or LLM-based systems.
• Proficiency in Python and ML/AI libraries such as Hugging Face Transformers, LangChain, PyTorch.

Responsibilities

• Contribute to requirements elicitation and document business requirements.
• Facilitate software design discussions and document decisions for the tech team.
• Participate in coding and integrate new features with a focus on stability.
• Conduct code reviews and maintain code repositories.
• Implement test strategies, analyze results, and coordinate bug fixes.
• Develop user training materials and support frameworks for new software.
• Resolve production issues and propose preventive strategies to improve reliability.
• Maintain detailed records of code, tests, and support activities.

Skills

Gen AI design & deployment

SDLC mastery

Cross-functional collaboration

Code reviews

Troubleshooting & testing

Documentation & training

Education

Bachelor’s degree or foreign equivalent

Tools

Python

FastAPI

Docker

LangGraph / LangChain

Job description

Infosys Topaz seeks a Technology Consultant 2 with strong Gen AI experience to design, develop, and deploy AI-enabled solutions. You will help elicit requirements, guide architecture discussions, and implement features in Python using LangGraph, LangChain, and modern ML tools.

You will participate in end-to-end SDLC, conduct code reviews, and improve system reliability. The role includes creating training materials and coordinating deployment with cross-functional teams in a dynamic environment.