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Infosys · 1 day ago

GenAI Engineer- Python

Charlotte, NC

Full-time

Hybrid

Mid Level

4+ years exp

Infosys is a global leader in next-generation digital services and consulting. They are seeking an AI/ML & Generative AI Engineer to design, develop, and deploy advanced AI solutions, collaborating with clients to address complex business challenges using modern cloud platforms.

ConsultingInformation ServicesInformation TechnologyIT ManagementSoftware

No H1B

Responsibilities

Collaborate with clients to understand complex business challenges

Architect scalable AI solutions

Deploy AI solutions using modern cloud platforms such as Azure ML and GCP AI Services

Qualification

Python programmingGenerative AIMLOpsBig Data technologiesCloud platformsML model developmentStakeholder managementDomain expertiseProblem-solving skillsCommunication skills

Required

Bachelor's degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education

Candidate must live within commuting distance of Charlotte, NC or be willing to relocate. This position may require travel in the US

At least 4 years of experience in Information Technology

Applicants authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time

At least 4 years of experience in Python programming, including OOPs, data structures (queues, stacks, linked lists), and API development

At least 3 years of experience in Big Data technologies (e.g., BigQuery, Hadoop)

At least 2 years of experience in cloud platforms (Azure, GCP) and their AI/ML services

At least 2 years of experience in ML model development, data engineering, and software engineering principles

At least 3 years of experience in MLOps and AI/ML deployment (e.g., SageMaker, Snowflake)

At least 2 years of hands-on experience in Generative AI, LLMs, and agentic frameworks