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Artificial Intelligence/AI Engineer (AWS/Agentic AI/GenAI)
Meet Greater Reading
40 minutes ago
Full-time
On-site
Reading, Pennsylvania, United States
Artificial Intelligence/AI Engineer (AWS/Agentic AI/GenAI)
Reading, PA OR Tampa, FL | Hybrid (2-3 days onsite per week) | Contract-to-Hire (or Direct Hire, client is flexible) One onsite interview is required | Local candidates to work onsite & appear for onsite interview Summary We are seeking an experienced AI Engineer to design, build, and deploy production-ready AI and machine learning solutions in a large enterprise environment. This is a hands-on engineering role focused on building intelligent applications, agentic AI workflows, and scalable ML solutions on AWS. The ideal candidate combines strong Python/software engineering skills with practical experience in Generative AI, machine learning, and cloud-based AI platforms. Responsibilities • Design and develop AI-powered applications and agentic workflows using Python 3.11+. • Build, train, deploy, and monitor ML models using Amazon SageMaker. • Develop end-to-end ML workflows covering feature engineering, deployment, monitoring, and model lifecycle management. • Build agentic and multi-agent AI solutions using LangGraph, CrewAI, AutoGen, or similar frameworks. • Work with LLMs, RAG architectures, prompt engineering, and knowledge retrieval. • Integrate AI agents with APIs, enterprise systems, databases, and external tools. • Utilize AWS Bedrock and emerging AgentCore capabilities for enterprise agentic AI. • Use Dataiku for data preparation, analytics, feature engineering, and ML workflows. • Partner with data scientists, architects, engineering teams, and business stakeholders to operationalize AI solutions. • Develop reusable AI components and deployment patterns with an emphasis on scalability, reliability, security, observability, and cost. Qualifications • Strong hands-on Python development experience. • Experience developing production AI/ML applications. • Hands-on Amazon SageMaker experience. • Experience with Generative AI, LLMs, RAG, and agentic AI architectures. • Experience with agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent. • Strong understanding of ML engineering, MLOps, model deployment, monitoring, and lifecycle management. • AWS cloud experience. • Experience integrating APIs, databases, or enterprise applications into AI solutions. Highly Preferred • Dataiku • AWS Bedrock / AgentCore • Model Context Protocol (MCP) • Vector databases and knowledge retrieval • LangChain or LlamaIndex • Docker, Kubernetes, Terraform, GitHub Actions, or CI/CD • Experience building AI solutions in a large enterprise environment
Reading, PA OR Tampa, FL | Hybrid (2-3 days onsite per week) | Contract-to-Hire (or Direct Hire, client is flexible) One onsite interview is required | Local candidates to work onsite & appear for onsite interview Summary We are seeking an experienced AI Engineer to design, build, and deploy production-ready AI and machine learning solutions in a large enterprise environment. This is a hands-on engineering role focused on building intelligent applications, agentic AI workflows, and scalable ML solutions on AWS. The ideal candidate combines strong Python/software engineering skills with practical experience in Generative AI, machine learning, and cloud-based AI platforms. Responsibilities • Design and develop AI-powered applications and agentic workflows using Python 3.11+. • Build, train, deploy, and monitor ML models using Amazon SageMaker. • Develop end-to-end ML workflows covering feature engineering, deployment, monitoring, and model lifecycle management. • Build agentic and multi-agent AI solutions using LangGraph, CrewAI, AutoGen, or similar frameworks. • Work with LLMs, RAG architectures, prompt engineering, and knowledge retrieval. • Integrate AI agents with APIs, enterprise systems, databases, and external tools. • Utilize AWS Bedrock and emerging AgentCore capabilities for enterprise agentic AI. • Use Dataiku for data preparation, analytics, feature engineering, and ML workflows. • Partner with data scientists, architects, engineering teams, and business stakeholders to operationalize AI solutions. • Develop reusable AI components and deployment patterns with an emphasis on scalability, reliability, security, observability, and cost. Qualifications • Strong hands-on Python development experience. • Experience developing production AI/ML applications. • Hands-on Amazon SageMaker experience. • Experience with Generative AI, LLMs, RAG, and agentic AI architectures. • Experience with agent orchestration frameworks such as LangGraph, CrewAI, AutoGen, or equivalent. • Strong understanding of ML engineering, MLOps, model deployment, monitoring, and lifecycle management. • AWS cloud experience. • Experience integrating APIs, databases, or enterprise applications into AI solutions. Highly Preferred • Dataiku • AWS Bedrock / AgentCore • Model Context Protocol (MCP) • Vector databases and knowledge retrieval • LangChain or LlamaIndex • Docker, Kubernetes, Terraform, GitHub Actions, or CI/CD • Experience building AI solutions in a large enterprise environment