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# Python Agentic AI Developer

- **Company:** AgreeYa Solutions, Inc.
- **Location:** St. Louis, MO, United States
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Unit Testing, Microsoft Azure, Code Review, Databases, Image Analysis, Continuous Integration, Distributed Systems, Identity and Access Management, JSON, Python (Programming Language), PostgreSQL, Role-Based Access Control, Search Technologies, Service Design, Software Engineering, SQLAlchemy, Data Streaming, WebSocket, Datadog, Data Logging, Large Language Models, Multi-Agent Systems, Prompt Engineering, Git, Fastapi, Pytest, Gitlab-ci, Kubernetes, Low Latency, Live Streaming, Api Design, Splunk, GPT, Docker, Microservices
- **Published:** September 29, 2026
- **Apply:** https://www.dice.com/job-detail/d309c9eb-7302-42ea-9b24-34778cf66674

## About the Role

Must-Have

 - 10+ years of software development with strong Python expertise in production environments
 - 2+ years hands-on LLM development (LangChain, LangGraph, or equivalent frameworks)
 - RAG pipeline experience - embeddings, vector search, re-ranking, answer generation
 - LLM APIs - OpenAI Chat Completions, Responses API, streaming, tool calling
 - Async Python - asyncio, httpx, FastAPI
 - Prompt engineering - system prompts, few-shot, structured JSON output
 - Circuit breaker patterns, retry logic, resilient service design
 - PostgreSQL and async ORMs (SQLAlchemy async / Alembic)
 - Git, CI/CD, Docker, Kubernetes basics
 - Strong system design skills - microservices, distributed systems, API design

Nice-to-Have

 - LangGraph StateGraph (conditional edges, node pipelines, compiled graphs)
 - Multi-agent systems - orchestration, routing, RBAC-based access control
 - Langfuse or similar LLM observability (tracing, token usage, latency)
 - WebSocket and SSE streaming protocols
 - Multi-modal AI (vision models, image analysis)
 - Vector databases (OpenSearch, Pinecone, pgvector)
 - AWS services (Aurora PostgreSQL, SSM, IAM, EKS)
 - Telecommunications or field service domain experience

Tech Stack

Category Technologies
Language Python 3.11+
Frameworks FastAPI, LangChain, LangGraph
LLM APIs Azure OpenAI (GPT-4)
Databases PostgreSQL (Aurora), OpenSearch (vector)
Messaging WebSocket, SSE, REST
Observability Langfuse, Datadog, Splunk
Infrastructure Docker, Kubernetes (EKS), AWS
CI/CD GitLab CI, Helm, ArgoCD
Package Mgmt uv (Python), pyproject.toml
Testing pytest, unittest, FastAPI TestClient

## Description

We are looking for a skilled AI/ML Developer to join our agentic platform team on a contractual basis. You will design,
develop, and deploy LLM-powered agents and pipelines that directly serve field technicians in production. You will work
closely with the platform architect and contribute to the core multi-agent orchestration system.
Key Responsibilities

 - Design and develop LLM-powered agents using LangGraph and LangChain frameworks
 - Build and enhance multi-agent orchestration pipelines with conditional routing, state management, and error recovery
 - Develop RAG pipelines with hybrid search (semantic + keyword), re-ranking, and Reciprocal Rank Fusion
 - Implement tool-calling agents with parallel API execution, sequential enrichment chains, and summarization
 - Build real-time streaming capabilities (WebSocket / SSE) for conversational AI
 - Integrate with Azure OpenAI APIs with circuit breaker patterns and fallback chains
 - Implement prompt engineering and dynamic prompt management (DB-backed with in-memory caching)
 - Design and implement multi-modal AI features (image analysis with vision models)
 - Write production-quality Python code with error handling, logging, observability, and unit tests
 - Participate in code reviews, architecture discussions, and sprint delivery