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# Agentic AI Developer

- **Company:** AgreeYa Solutions, Inc.
- **Location:** Alpharetta, GA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Computer Programming, Databases, Continuous Integration, Software Debugging, Memory Management, JSON, Python (Programming Language), Search Technologies, Software Engineering, Systems Architecture, TypeScript, Openapi, Enterprise Software Applications, ReactJS, Large Language Models, Multi-Agent Systems, Integration Tests, Kubernetes, Information Technology, Low Latency, Asynchronous Programming, Restful APIs, Docker, Microservices
- **Published:** August 28, 2026
- **Apply:** https://www.dice.com/job-detail/94cefe73-439d-41ef-81d5-d697c6a0a687

## About the Role

* Bachelor s or master s degree in computer science, AI, Software Engineering, or equivalent practical experience with 1 2+ years focused on LLM/AI applications.
 * Programming Skills: Expert-level proficiency in Python (TypeScript/JavaScript experience is a plus).
 * Agent Frameworks: Demonstrated experience building with frameworks like LangGraph, CrewAI, Microsoft AutoGen, LlamaIndex Agents, or Semantic Kernel.
 * API & Tool Integration: Proven track record building RESTful APIs, OpenAPI specifications, function calling architectures, and model tool definitions.
 * Vector Databases & RAG: Hands-on experience with vector search engines (Pinecone, Qdrant, Milvus, Weaviate, or Chroma) and hybrid retriever architectures.
 * Software Engineering Fundamentals: Strong background in asynchronous programming, microservices, Docker/Kubernetes, CI/CD, and unit/integration testing for non-deterministic AI systems.

## Description

* Agent Design & Orchestration Architect and implement autonomous AI agents using modern frameworks (e.g., LangGraph, CrewAI, AutoGen, LlamaIndex, or custom orchestration loops).
 * Design agent reasoning architectures, including ReAct loops, Plan-and-Solve patterns, Reflection/Self-Correction mechanisms, and hierarchical multi-agent structures.
 * Construct robust tool-use pipelines enabling agents to seamlessly call external APIs, query databases, execute code, and interact with enterprise software.
 * System Architecture & Integration Integrate Long-Term Memory systems (vector databases, semantic search, key-value state stores) and Short-Term/Context Memory management strategies. Implement structured input/output parsing (Pydantic, JSON Schema) to guarantee reliable communication between model calls and execution environments.
 * Build fallback mechanisms, human-in-the-loop (HITL) checkpoints, and deterministic guards around non-deterministic AI decisions.
 * Monitoring, Evaluation & Optimization Establish evaluation pipelines (using tools like Ragas, TruLens, or LangSmith) to benchmark agent accuracy, execution speed, trajectory quality, and tool failure rates. Monitor runtime performance, API usage costs, latency, and context-window token optimization across complex multi-step trajectories.
 * Debug non-deterministic failures, looping behaviors, and hallucinations in multi-step agent execution paths.


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