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Langgraph Jobs in Florida (NOW HIRING)

Design agentic workflows using LangChain and LangGraph. * Implement short-term and long-term memory strategies for LLM-based systems. * Optimize prompts, retrieval pipelines, and orchestration logic.

Build and deploy applications leveraging LangChain, LangGraph, or other GenAI frameworks * Implement Retrieval-Augmented Generation (RAG) pipelines and integrate Large Language Models (LLMs)

New

Responsibilities : • Design scalable, maintainable AI solutions that integrate Langchain, LangGraph, and RAG methodologies to enhance knowledge discovery and conversational AI capabilities. • ...

Gen AI Tech Lead

Tampa, FL · On-site

$132K - $162K/yr

Responsibilities : • Design scalable, maintainable AI solutions that integrate Langchain, LangGraph, and RAG methodologies to enhance knowledge discovery and conversational AI capabilities. • ...

Senior Agentic (AI) Engineer

Orlando, FL · On-site +1

$97K - $134K/yr

Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks. * Build the retrieval layer powering our ...

Senior Agentic (AI) Engineer

Miami, FL · On-site +1

$99K - $137K/yr

Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks. * Build the retrieval layer powering our ...

Senior Agentic (AI) Engineer

Tampa, FL · On-site +1

$98K - $135K/yr

Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks. * Build the retrieval layer powering our ...

Senior Agentic (AI) Engineer

Orlando, FL · On-site +1

$97K - $134K/yr

Architect agent graphs in LangGraph (or comparable - CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks. * Build the retrieval layer powering our ...

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Showing results 1-20

Langgraph information

What is the difference between Langgraph vs Data Analyst?

AspectLanggraphData Analyst
Required CredentialsTypically requires knowledge of language processing and graph databasesUsually requires a degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI research labs, data-driven organizationsBusiness, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and NLP projectsEstablished role in data interpretation and reporting

While Langgraph focuses on language processing and graph database integration, Data Analysts primarily interpret and visualize data to support business decisions. Both roles require analytical skills, but Langgraph specialists often have a background in AI and NLP, whereas Data Analysts typically hold degrees in statistics or related fields.

What are the key skills and qualifications needed to thrive as a Langgraph engineer, and why are they important?

To thrive as a Langgraph engineer, you need a strong background in software engineering, proficiency in Python, and a solid understanding of AI/ML concepts, usually supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), API integrations, and version control systems such as Git is essential. Effective problem-solving, collaboration, and clear communication are crucial soft skills for working with multidisciplinary teams and resolving complex issues. These capabilities are important because they enable the development, scaling, and maintenance of robust AI-driven applications using the Langgraph platform.

What is a Langgraph?

Langgraph is a framework designed to build, manage, and orchestrate complex workflows for large language models (LLMs). It allows developers to create directed graphs of language model prompts, tools, and custom logic, making it easier to design multi-step, stateful AI applications. Langgraph is especially useful for building conversational agents, automated workflows, and other applications that require LLMs to interact with data or tools in a structured way.

What are some common challenges faced by Langgraph developers when integrating their workflow with existing AI infrastructure?

Langgraph developers often encounter challenges when integrating their workflow with existing AI infrastructure, such as ensuring compatibility with various large language models and managing data flow across multiple APIs. Coordination with data engineers and machine learning specialists is crucial to align model outputs with business requirements, and adapting to rapidly evolving technologies can require continuous learning. Additionally, optimizing performance and maintaining security standards during integration are key considerations to ensure successful deployment.
What cities in Florida are hiring for Langgraph jobs? Cities in Florida with the most Langgraph job openings:
Infographic showing various Langgraph job openings in Florida as of July 2026, with employment types broken down into 90% Full Time, 5% Part Time, 1% Temporary, and 4% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution.
Information Technology_USA - USA_Developer

Information Technology_USA - USA_Developer

Real Soft, Inc.

Jacksonville, FL • On-site

Contractor

Re-posted 17 days ago


Job description

Local to Charlotte Only!
JD
Must Have Technical/Functional Skills
• Python (automation, backend services).
• JavaScript/TypeScript
• LangChain and/or LangGraph hands-on experience.
• Docker and container-based deployments.
• AWS Cloud Practitioner-level knowledge with hands-on exposure.
Roles & Responsibilities
Design, develop, and support cloud-native automation and AI agent workflows using Python, RPA,
and LLM orchestration frameworks (LangChain / LangGraph), deployed on AWS using containerized
architectures.Responsibilities
Build AI agents using LangChain and LangGraph to orchestrate tools, APIs, and workflows.
Integrate automations with enterprise systems via REST APIs and databases.
Containerize services using Docker and support CI/CD pipelines.
• Deploy and operate solutions on AWS (IAM, S3, Lambda, ECS/Fargate, CloudWatch).
• Implement logging, error handling, and basic monitoring.
• Collaborate with onshore architects and follow defined architecture standards
Role Descriptions: Design| develop| and support cloud-native automation and AI agent workflows using Python| RPA| and LLM orchestration frameworks (LangChain / LangGraph)| deployed on AWS using containerized architectures.ResponsibilitiesBuild AI agents using LangChain and LangGraph to orchestrate tools| APIs| and workflows.Integrate automations with enterprise systems via REST APIs and databases.Containerize services using Docker and support CI/CD pipelines.Deploy and operate solutions on AWS (IAM| S3| Lambda| ECS/Fargate| CloudWatch).Implement logging| error handling| and basic monitoring.Collaborate with onshore architects and follow defined architecture standards
Essential Skills: Design| develop| and support cloud-native automation and AI agent workflows using Python| RPA| and LLM orchestration frameworks (LangChain / LangGraph)| deployed on AWS using containerized architectures.ResponsibilitiesBuild AI agents using LangChain and LangGraph to orchestrate tools| APIs| and workflows.Integrate automations with enterprise systems via REST APIs and databases.Containerize services using Docker and support CI/CD pipelines.Deploy and operate solutions on AWS (IAM| S3| Lambda| ECS/Fargate| CloudWatch).Implement logging| error handling| and basic monitoring.Collaborate with onshore architects and follow defined architecture standards
Desirable Skills:
Keyword:
Skills: Digital : Python
Experience Required: 4-6, Project Code :