Senior AI Engineer: AWS, GenAI & Agentic Workflows (Hybrid)

InSource, Inc; Reading (Berks County); Hybrid; USD 120,000 - 160,000; Full time

Job summary

InSource, Inc. is seeking an AI Engineer to design, build, and deploy production-ready AI solutions in a large enterprise environment. The role emphasizes agentic AI workflows and scalable ML on AWS, combining strong Python engineering with practical GenAI experience.

You will work across functions to operationalize AI, build reusable components, and ensure reliability, security, observability, and cost control in hybrid onsite settings in Reading, PA or Tampa, FL.

Qualifications

• Hands-on experience with Amazon SageMaker in production
• Experience with Generative AI, LLMs, RAG and agentic AI architectures
• Experience with agent orchestration frameworks (LangGraph, CrewAI, AutoGen)
• Strong ML engineering, MLOps, deployment, monitoring and lifecycle management
• Experience API/database integration into AI solutions

Responsibilities

• Design and develop AI-powered applications and agentic workflows using Python 3.11+.
• Build, train, deploy, and monitor ML models with SageMaker.
• Develop end-to-end ML workflows including feature engineering, deployment and monitoring.
• Create agentic AI solutions with LangGraph, CrewAI, AutoGen or equivalents.
• Work with LLMs, prompt engineering, and knowledge retrieval.
• Integrate AI agents with APIs, databases and enterprise systems.
• Leverage AWS Bedrock and AgentCore for enterprise AI.
• Use Dataiku for data prep and ML workflows.
• Collaborate with data scientists, architects and stakeholders to operationalize AI solutions.

Skills

SageMaker

Generative AI

LLMs

RAG

Agentic AI

AI orchestration

ML engineering

MLOps

API integration

Tools

AWS Bedrock

Dataiku

LangGraph

CrewAI

AutoGen

Docker

Kubernetes

Terraform

GitHub Actions

Job description

InSource, Inc. is seeking an AI Engineer to design, build, and deploy production-ready AI solutions in a large enterprise environment. The role emphasizes agentic AI workflows and scalable ML on AWS, combining strong Python engineering with practical GenAI experience.

You will work across functions to operationalize AI, build reusable components, and ensure reliability, security, observability, and cost control in hybrid onsite settings in Reading, PA or Tampa, FL.