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Langgraph Jobs (NOW HIRING)

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 ...

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 ...

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 ...

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 ...

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 ...

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.

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 ...

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 ...

LangGraph, LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen. Agentic AI Concepts: Multi-Agent Systems (MAS), Agent Planning, Tool Calling, Memory Management, Human-in-the-Loop (HITL) workflows.

Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows. • Drive ...

Showing results 41-60

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:

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.

$100K - $120K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago


Job description

Skill: Agentic AI Developer
  • The Agentic AI Developer will design, build, and operationalize governed AI agent systems that autonomously plan, reason, and execute complex workflows across enterprise data and risk platforms.
  • This role focuses on developing multi agent, event driven AI solutions using Python, LangChain, LangGraph, and Azure AI Foundry, with strong emphasis on explainability, human in the loop control, and regulatory readiness.

Primary Skills:
  • 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, CrewAI).
  • Reasoning & Planning: Implement advanced prompting strategies, such as chain-of-thought, reflection, and self-correction loops to enhance agent decision-making.
  • Tool Integration: Connect AI agents to APIs, databases, and third-party SaaS platforms to enable autonomous action-taking.
  • Memory & Context: Design short-term and long-term memory systems .
  • (RAG, vector databases) so agents can maintain state and context over long-running workflows.
  • Production Deployment: Transition prototypes from research to production-ready systems, ensuring low latency, high accuracy, and observability (e.g., using Amazon CloudWatch, LangSmith).
  • Safety & Governance: Implement AI guardrails, human-in-the-loop approval steps, and audit trails to ensure ethical and secure operation.

Salary Range - $110,000-$120,000 a year
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.