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Langgraph Jobs (NOW HIRING)

Tata Consultancy Service Limited

Engineer

Pittsburgh, PA · On-site

$100K - $120K/yr

Python, LangChain, LangGraph, Azure AI Foundry Roles & Responsibilities: * Agentic System Design: Architect, build, and optimize AI agents using multi-agent frameworks (e.g., LangGraph, AutoGen ...

ApTask

.Net Developer with AI

Charlotte, NC · On-site

NET Full Stack Developer with expertise in Angular , Generative AI , LangChain, and LangGraph to design, develop, and implement intelligent web applications. The ideal candidate will have strong ...

Turing

Forward Deployed AI Engineer

New York, NY

In this role, you'll partner directly with customers to design, build, and deploy intelligent applications using Python, Langchain/LangGraph, and large language models. You'll bridge engineering ...

Judge Group, Inc.

Software Engineer

Charlotte, NC · On-site

$69 - $74/hr

LangGraph About the Role We are seeking a Senior AI Developer to architect, build, and deploy enterprise-scale Generative AI solutions. This role will focus on designing agentic workflows, Retrieval ...

GLOBAL IT CON LLC

Senior AI/ML Engineer

Saint Louis, MO · On-site

$99K - $136K/yr

Key Responsibilities - Design and develop LLM-powered agents using LangGraph and LangChain frameworks - Build and enhance multi-agent orchestration pipelines with conditional routing, state ...

WorkNovas LLC

Gen AI Engineer

Sunrise, FL · On-site

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.

BI Solutions Inc

Senior Agentic AI Developer

Coppell, TX · On-site

$50.75 - $67/hr

The ideal candidate has experience with LangGraph, IBM Watsonx Orchestrate, and Google Vertex AI, and can design scalable services that incorporate advanced reasoning, workflow orchestration, and ...

Nastech Global

AI Engineer

Cupertino, CA · On-site

Hands-on experience with LangGraph for workflow orchestration * Expertise in building Retrieval-Augmented Generation (RAG) pipelines * Knowledge of semantic layers and knowledge graphs for structured ...

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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.

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What states have the most Langgraph jobs?

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What job categories do people searching Langgraph jobs look for?

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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.

Machine Learning Engineer

Sunrise, FL • On-site

Tata Consultancy Service Limited
See more jobs at Tata Consultancy Service Limitedexternal

$90K - $110K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago

Job description

Role - Machine Learning Engineer
Experience Required -8+ Years
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). Design agentic workflows using LangChain and LangGraph.
Must Have Technical/Functional Skills:
We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAI use cases, from model selection to production-ready systems. Key Responsibilities Develop and productionize GenAI applications using LLMs (open-source and closed-source). 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.
• Collaborate with product and platform teams to deliver scalable AI solutions.
Required Qualifications
• Strong experience with LLMs (e.g., OpenAI, Anthropic, Llama, Mistral)
• Hands-on experience with LangChain and/or LangGraph.
• Solid understanding of LLM memory architecture and state management.
• Proficiency in Python and ML engineering best practices.
Nice to Have
• Experience with GCP services (e.g., Vertex AI, BigQuery, GCS).
• Experience deploying ML/GenAI systems in production environments.
• data scientist
• Can do ML model
Roles & Responsibilities
• Design, develop, and deploy GenAI applications using LLMs.
• Build and implement agentic workflows using LangChain/LangGraph.
• Develop ML models and production-ready AI solutions.
• Implement and manage LLM memory and state management strategies.
• Optimize prompts, retrieval pipelines, and orchestration workflows.
• Collaborate with product and platform teams to deliver scalable AI solutions.
• Deploy, monitor, and maintain AI/ML systems in production environments.
• Evaluate and integrate open-source and proprietary LLMs.
Base Salary Range : $90,000 to $110,000 Per Annum
TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options : Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

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