GenAI Engineer at Global Payments

Alpharetta, Georgia, United States

Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

NoVisa

Payments, FinTechIndustries

Bachelor’s degree in Computer Science, Engineering, or a related field
4+ years of experience in AI/ML engineering, with a focus on Generative AI
Proficiency in programming languages such as Python
Strong understanding of Generative AI models (e.g., GPT, Transformer architectures) and experience in distilling, tuning, and training them
Familiarity with Retrieval Augmented Generation (RAG) techniques and their implementation
Experience with agentic AI concepts and developing autonomous AI workflows
Hands-on experience with GCP Vertex AI, AWS Bedrock + Sagemaker, and Snowflake Cortex platforms and their AI/ML capabilities
Experience with machine learning frameworks (TensorFlow, PyTorch, Hugging Face Transformers)
Experience with AI frameworks such as LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, etc
Experience with Natural Language Processing (NLP) and building conversational AI agents
Experience with vector databases (e.g., Pinecone, MongoDB Atlas, OpenSearch, pgVector, FAISS, Qdrant, etc.)
Experience building production-grade AI/ML systems at scale
Knowledge of MLOps practices, including model deployment and lifecycle management
Excellent problem-solving and analytical skills
Excellent communication and collaboration skills

Design, develop, implement, test, and maintain Generative AI models and agentic workflows using GCP Vertex AI, AWS Bedrock, and Snowflake Cortex
Build and integrate Retrieval Augmented Generation (RAG) systems to ground the responses of AI solutions with up-to-date and relevant data
Fine-tune and evaluate foundation models using both proprietary and open-source technology
Develop agentic architectures using tools like LangGraph, CrewAI, AutoGen, and others to orchestrate multi-step reasoning, planning, and tool use
Build and optimize AI agents that can interface with MCP servers, APIs, databases, take contextual actions, and autonomously execute business workflows
Collaborate closely with data scientists, data engineers, and stakeholders to understand requirements and deliver AI solutions that meet business needs
Implement best practices for model deployment, monitoring, validation, and retraining on GCP Vertex AI, AWS Bedrock, and Snowflake Cortex
Work with cross-functional IT and business teams in an Agile environment to deliver successful AI solutions
Document processes, models, and configurations for knowledge sharing and compliance
Stay current with the latest in generative AI research and translate breakthroughs into applied business solutions