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Langgraph Jobs (NOW HIRING)

Droisys

Generative AI LangGraph experience

Plano, TX · On-site

Generative AI Engineer with LangGraph experience Plano, TX- Fully Onsite from Day-1 Core Technical Skills: * Python Programming: Advanced proficiency in Python, including experience with asynchronous ...

Salesforce

DS with GEN AI

Plano, TX · On-site

$14.25 - $18.50/hr

Hands-on experience building, deploying, and maintaining applications using LangChain and LangGraph frameworks. • Large Language Models (LLMs): In-depth understanding and practical experience with ...

Salesforce

DS with GEN AI

Murphy, TX

$14.25 - $18.50/hr

Hands-on experience building, deploying, and maintaining applications using LangChain and LangGraph frameworks. • Large Language Models (LLMs): In-depth understanding and practical experience with ...

IT America Inc

Agentic AI Engineer Lead

Dallas, TX · On-site

$101K - $133K/yr

Primary - LangGraph, ReAct, LangChain, LlamaIndex, Python Secondary - GCP, Google Spanner/Neo4j, CrewAI, AutoGen, OpenAI The Agentic AI Lead is a pivotal role responsible for driving the research ...

VDart, Inc.

AI Engineer - W2

Charlotte, NC

Job Title/Role AI Engineer Mandatory Skills LangChain/LangGraph, Google ADK Years of Experience Required 8+ JD Strong experience in Python (8+ years) - LangChain/LangGraph, Google ADK - Design ...

eClerx

Senior AI Developer

Manhattan, NY

$125K - $140K/yr

Leverage LangGraph's stateful graph execution model to build resilient, interruptible, and human-in-the-loop agentic workflows * Integrate LLM-powered agents with external APIs, databases, and ...

eClercx

Senior AI Developer

Manhattan, NY · On-site

$125K - $140K/yr

Leverage LangGraph's stateful graph execution model to build resilient, interruptible, and human-in-the-loop agentic workflows * Integrate LLM-powered agents with external APIs, databases, and ...

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All JobsLanggraph Jobs

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.
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Langgraph jobs near you
Infographic showing various Langgraph job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution.

Java Developer - LangGraph

Texas State Library and Archives Commision

Dallas, TX • On-site

$47 - $61/hr

Full-time

Posted 22 days ago

Job description

We are seeking a skilled Java Developer with hands-on experience in LangGraph to join our growing engineering team. You will be responsible for developing, integrating, and maintaining high-performance applications that utilize language models within a graph-based computational workflow. This role offers a unique opportunity to work at the intersection of AI, distributed systems, and backend Java development.
Key Responsibilities:
  • Design, develop, and maintain Java-based backend services and APIs.
  • Integrate and manage LangGraph workflows, leveraging LLMs to build dynamic, branching applications.
  • Collaborate with AI engineers to integrate language models (e.g., OpenAI, Hugging Face) into existing infrastructure.
  • Optimize performance and scalability of graph-based systems for production environments.
  • Write clean, maintainable, and testable code.

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