Agentic AI Developer
THE JUDGE GROUP, INC.
Schaumburg, United States of America
yesterday
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Compensation
$ 135KJob location
Schaumburg, United States of America
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Python
Knowledge-Based Systems
TensorFlow
Reinforcement Learning
Google Cloud Platform
Enterprise Software Applications
Large Language Models
Multi-Agent Systems
Generative AI
Virtual Agents
Job description
Our client is seeking a highly skilled Agentic AI Developer to design and deliver cutting-edge AI-driven systems. This role focuses on building agent-based architectures powered by large language models (LLMs) to enable intelligent automation and advanced decision-making capabilities.
You will play a key role in developing scalable, production-ready AI solutions that integrate with enterprise systems and drive real business impact. What You'll Do
- Design, develop, and deploy agent-based AI systems
- Build and manage multi-agent architectures for complex workflows
- Integrate large language models (LLMs) into enterprise applications
- Develop agentic solutions using frameworks such as:
- LangChain
- AutoGen
- CrewAI
- Semantic Kernel
- Implement and optimize Retrieval-Augmented Generation (RAG) architectures
- Integrate AI solutions with enterprise knowledge systems and data sources
- Ensure performance, scalability, and reliability of deployed AI systems
- Collaborate with cross-functional teams to deliver production-ready AI features
Requirements
- Strong experience developing agentic AI systems
- Hands-on experience with Agentic AI tools (e.g., Google AgentSpace)
- Expertise working with LLMs (Large Language Models)
- Proficiency in Python
- Experience with AI/ML frameworks and libraries
- Solid understanding of:
- LLMs
- Agentic AI concepts
- Reinforcement learning
- Experience building and deploying RAG architectures
- Cloud experience with Azure, AWS, or Google Cloud
Nice to Have
- Experience deploying AI solutions into production environments
- Familiarity with vector databases or embeddings
- Background in enterprise-scale AI implementations