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Langgraph Jobs (NOW HIRING)

TekCommands Inc

Sr GenAI + LangGraph Developer

Dallas, TX · On-site

$54 - $71.25/hr

Client is looking for - Hands on GenAI + LangGraph candidate assuming should be very good with GenAI Fundamentals, Prompt Engineering, LLM, Agentic AI, Agentic System Design, LangChain, LangGraph ...

Info Dinamica Inc

Sr LangGraph Developer - Only W2

Dallas, TX · On-site

$54.25 - $71.50/hr

Job Title: Sr LangGraph Developer Onsite in Dallas, TX W2 Position Job Summary: We are looking for a highly experienced and technically elite Senior LangGraph Developer to architect and implement ...

New

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 ...

HeadHR

NY · On-site

$130 - $160/hr

As Principal AI Engineer you are the technical owner of the AI core. You lead the audit of the existing codebase, define the architecture we evolve toward, build the test and evaluation harness that ...

Cliff Services Inc

Python / GenAI Developer

Dallas, TX · On-site

$50 - $68.75/hr

Dallas, TX Position Overview We are seeking Junior and Senior Python Developers specializing in Generative AI and LangGraph to join our team in Dallas. You will build and scale AI-driven applications ...

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 ...

eClerx LLC

Senior AI Developer

Manhattan, NY · On-site

$125 - $140/hr

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 ...

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Langgraph information

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 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 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.

More about Langgraph jobs

What cities are hiring for Langgraph jobs?

Cities with the most Langgraph job openings:

What states have the most Langgraph jobs?

States with the most job openings for Langgraph jobs include:

What job categories do people searching Langgraph jobs look for?

The top searched job categories for Langgraph jobs are:

Langgraph jobs near you
Infographic showing various Langgraph job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 1% Part Time, and 6% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Sr GenAI + LangGraph Developer

TekCommands Inc

Dallas, TX • On-site

$54 - $71.25/hr

Contractor

Posted 5 days ago

Job description

Client needs a GenAI background candidate who is strong with AI fundamentals, really worked into different use cases and can code without AI assistance. Since we faced many issues with candidates taking external help during interviews and were caught during client round , we have a mandate to have the internal + client round in -person.
Client is looking for - Hands on GenAI + LangGraph candidate assuming should be very good with GenAI Fundamentals, Prompt Engineering, LLM, Agentic AI, Agentic System Design, LangChain, LangGraph, Monitoring , CI/CD process. Coding expertise without using AI agent is very essential( which is part of evaluation)
Way it goes –
* Round 1(video 30 minutes) – Checking potentiality of candidate according to requirement.
* Round 2 (in-person Dallas/Charlotte client office) – Some additional theoretical + coding challenge( without AI assistance- pseudo, look alike which includes tool calling and intent routing)
* Client Round (in-person Dallas/Charlotte client office) – Technical + Coding
Job Summary:
We are looking for a highly experienced and technically elite Senior LangGraph Developer to architect and implement cutting-edge agentic workflows using LangGraph. This role demands deep expertise in building stateful, multi-agent systems that leverage LLMs for complex decision-making, orchestration, and automation. You will be responsible for designing resilient, scalable LangGraph architectures that power intelligent applications across domains.
Locations: Dallas(Primary), Charlotte(Secondary) – Hybrid mode(work from office 3 days a week)
Key Responsibilities:
• Design and implement advanced LangGraph workflows with complex node logic, branching, and memory management.
• Lead the development of agentic systems that interact, reason, and adapt dynamically.
• Optimize performance and scalability of LangGraph graphs in production environments.
• Integrate LangGraph with external APIs, databases, and LLMs to create seamless, intelligent pipelines.
• Mentor junior developers and establish best practices for LangGraph development.
• Collaborate with AI researchers and product teams to translate abstract ideas into robust LangGraph implementations.
• Design , create and deploy AgenticAI models at production level.
Required Skills & Experience:
• 10+ years in software engineering , with at least 2+ years in LangGraph or agentic frameworks .
• Expert-level proficiency in Python , asynchronous programming, and graph-based computation.
• Deep understanding of LLM orchestration , memory management, and stateful agent design.
• Experience with LangChain, OpenAI, Anthropic, or similar LLM platforms .
• Strong grasp of workflow debugging, graph visualization, and LangGraph Studio .
• Proven ability to build production-grade agentic systems with high reliability and fault tolerance.
• Proficient with AgenticAI models.
• Vetted with Evaluation metrics(RAG, Batch processing, AgenticAI).