Hiring: GenAI Engineer

Amazon.com, Inc.

Charlotte, NC, United States

about 1 month ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Compensation

$110,000.0 - $145,000.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Agile Methodology Artificial Intelligence Amazon Web Services Microsoft Azure Cloud Engineering Python (Programming Language) Salesforce.Com Software Deployment Software Engineering Workflow Management Systems Google Cloud Chatbots

+12 more

Large Language Models Multi-Agent Systems Prompt Engineering Generative AI Git Data Management Api Design Restful APIs Software Version Control Api Management Servicenow Microservices

Job description

Seeking an experienced GenAI Engineer to design, develop, and implement enterprise-grade AI solutions. The ideal candidate will have expertise in Large Language Models (LLMs), AI agents, workflow automation, API integrations, and cloud-based AI services. This role will focus on building scalable AI-powered applications, copilots, and intelligent automation solutions while ensuring security, governance, and enterprise compliance standards.

Requirements

Strong experience with Generative AI, Large Language Models (LLMs), and AI-powered application development.
Hands-on experience building AI Agents, Copilots, Chatbots, and Workflow Automation solutions.
Expertise in Prompt Engineering, Prompt Optimization, and AI Workflow Design.
Experience with AI orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or similar technologies.
Strong knowledge of Retrieval-Augmented Generation (RAG), Vector Databases, Embeddings, and Enterprise Knowledge Integration.
Experience integrating AI solutions with enterprise platforms such as ServiceNow, Salesforce, Data Platforms, and internal applications.
Strong API development and integration experience using REST APIs, Microservices, and Service Orchestration patterns.
Proficiency in Python and experience developing AI/ML-based applications.
Experience with cloud platforms including AWS, Azure, or Google Cloud Platform (GCP), preferably Azure OpenAI, AWS Bedrock, or Google Vertex AI.
Knowledge of enterprise architecture, scalable application design, and production deployment of AI solutions.
Understanding of AI Security, Data Privacy, Governance, Responsible AI, and Model Risk Management.
Experience working with CI/CD pipelines, Git-based version control, and Agile development methodologies.

Preferred Skills

Experience deploying enterprise AI solutions into production environments.
Familiarity with AI monitoring, evaluation frameworks, and model performance optimization.
Knowledge of compliance, regulatory requirements, and AI governance frameworks.