Overview
Hybrid
Depends on Experience
Contract - W2
Contract - 60 Month(s)
No Travel Required
Skills
AI/ML development
Python
PyTorch or TensorFlow
LangChain
LangGraph
AutoGPT
ReAct
or similar agentic architectures
Job Details
Key Responsibilities:
- Design and develop autonomous, goal-directed agent systems using LLMs, planning algorithms, and reinforcement learning.
- Integrate memory, tools, and feedback mechanisms into agentic workflows for continuous learning and adaptability.
- Implement multi-agent systems for collaborative task execution and coordination.
- Build and maintain toolchains and frameworks for agent planning, reasoning, execution, and monitoring.
- Collaborate with researchers and engineers to prototype and deploy agentic solutions in production.
- Ensure safety, explainability, and reliability of agentic AI systems.
- Stay current with advancements in autonomous AI, cognitive architectures, and agent frameworks (e.g., LangGraph, AutoGPT, CrewAI).
- Write clean, testable, and efficient code with appropriate documentation and design patterns.
Required Qualifications:
- Bachelor s or Master s in Computer Science, Artificial Intelligence, or related field.
- 5 7 years of experience in AI/ML development, with at least 1 2 years focused on autonomous or agentic AI systems.
- Strong programming skills in Python (or similar), and experience with AI/ML frameworks such as PyTorch or TensorFlow.
- Experience with one or more of: LangChain, LangGraph, AutoGPT, ReAct, or similar agentic architectures.
- Solid understanding of LLMs, prompt engineering, and tool integration (APIs, plugins, retrieval-augmented generation).
- Familiarity with planning algorithms, reinforcement learning, or symbolic reasoning.
- Experience deploying scalable AI systems in cloud environments (AWS, Google Cloud Platform, or Azure)
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.