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Langgraph Jobs in Chicago, IL (NOW HIRING)

Neshent Technologies

Applied AI Architect

Skokie, IL

Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK. * Strong Python development skills for production AI/ML applications. * Experience with CI/CD ...

Neshent Technologies

Applied AI Architect

Lyons, IL

Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK. * Strong Python development skills for production AI/ML applications. * Experience with CI/CD ...

Neshent Technologies

Applied AI Architect

Glencoe, IL · On-site

Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK. * Strong Python development skills for production AI/ML applications. * Experience with CI/CD ...

Neshent Technologies

Applied AI Architect

Oak Brook, IL · On-site

Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK. * Strong Python development skills for production AI/ML applications. * Experience with CI/CD ...

US Bank

Lead AI Platform Engineer

Chicago, IL · On-site

$105K - $139K/yr

Build intelligent systems using frameworks such as LangChain, LangGraph, AWS Bedrock, and Microsoft Foundry Agent Service * Evaluate emerging tools and frameworks to continuously improve solution ...

Neshent Technologies

Applied AI Architect

Wood Dale, IL · On-site

Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK. * Strong Python development skills for production AI/ML applications. * Experience with CI/CD ...

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Showing results 21-40

All JobsLanggraph JobsLanggraph Jobs in Chicago, IL

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.

What are popular job titles related to Langgraph jobs in Chicago, IL?

For Langgraph jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Langgraph jobs in Chicago, IL look for?

The top searched job categories for Langgraph jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Langgraph jobs?

Cities near Chicago, IL with the most Langgraph job openings:

Langgraph jobs near you
Infographic showing various Langgraph job openings in Chicago, IL as of August 2026, with employment types broken down into 91% Full Time, 4% Part Time, and 5% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

Applied AI Architect

Neshent Technologies

Glen Ellyn, IL • On-site

Full-time

Posted 20 days ago

Job description

We are looking for an Applied AI Architect with strong hands-on experience in AI/ML architecture, development, and production deployment. The ideal candidate will have expertise in Databricks, Azure AI Foundry, LLM applications, RAG, and multi-agent systems.

Must-Have Technical Skills
  • Strong hands-on experience in AI/ML development and production deployment.
  • Experience with Databricks, MLflow, Unity Catalog, Delta Lake, and model serving.
  • Experience with Azure AI Foundry and modern AI/ML platforms.
  • Strong knowledge of RAG and LLM application architecture.
  • Experience building multi-agent systems and workflows.
  • Experience with MCP/tool calling and frameworks such as LangGraph, Semantic Kernel, or OpenAI Agents SDK.
  • Strong Python development skills for production AI/ML applications.
  • Experience with CI/CD, MLOps, and AIOps.
  • Knowledge of LLM/RAG/agent evaluation, observability, tracing, and monitoring.
  • Experience with production debugging and performance optimization.
  • Ability to create reusable AI accelerators, templates, skills, and reference implementations.
Roles & Responsibilities
  • Define and implement AI/ML architecture and solutions.
  • Work closely with engineering and business teams to build and deploy AI models.
  • Design and develop LLM, RAG, and multi-agent solutions.
  • Establish best practices for AI evaluation, deployment, monitoring, and production support.
  • Improve and standardize applied AI delivery patterns.
  • Accelerate AI adoption through reusable components, templates, and reference architectures.
  • Provide technical leadership and guidance to AI/ML engineering teams.

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