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Langgraph Jobs in Missouri (NOW HIRING)

Hands-on experience with LangGraph or similar agent orchestration frameworks. * Experience building AI workflows that leverage tools, APIs, and external systems. * Experience with AI evaluation ...

LangGraph * AI Workflow Orchestration * REST APIs DevOps * Git * Deployment Automation Observability * OpenTelemetry * Performance Optimization Secondary Skills (Good to Have) * LangChain * CrewAI

Senior AI Engineer

O Fallon, MO · Hybrid

$97K - $134K/yr

Roles & Responsibilities Architect and lead the development of multi-agent AI systems using frameworks such as LangGraph, CrewAI, and AutoGen - enabling autonomous reasoning, tool use, inter-agent ...

Senior AI Engineer

O Fallon, MO · On-site

$97K - $134K/yr

Roles & Responsibilities • Architect and lead the development of multi-agent AI systems using frameworks such as LangGraph, CrewAI, and AutoGen - enabling autonomous reasoning, tool use, inter ...

AI Engineer

Saint Louis, MO · On-site

$150 - $200/hr

Design, build, and deploy complex AI agents using LangChain and LangGraph. You will own the core logic that automates intricate decision‑making within the claims lifecycle. * Master Prompt ...

Design, build, and deploy complex AI agents using LangChain and LangGraph. You will own the core logic that automates intricate decision-making within the claims lifecycle. * Master Prompt & Context ...

Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP transformation programs for large enterprises The wage range for this role takes into account the wide ...

Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP transformation programs for large enterprises The wage range for this role takes into account the wide ...

Product Designer

California, MO · On-site

$150 - $200/hr

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched ...

Showing results 21-40

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 Missouri?

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

What job categories do people searching Langgraph jobs in Missouri look for?

The top searched job categories for Langgraph jobs in Missouri are:

What cities in Missouri are hiring for Langgraph jobs?

Cities in Missouri with the most Langgraph job openings:

Infographic showing various Langgraph job openings in Missouri as of August 2026, with employment types broken down into 1% Internship, 88% Full Time, 5% Part Time, and 6% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution.

Artificial Intelligence Architect

Long Finch Technologies

Lake Saint Louis, MO

Full-time

Posted 10 days ago


Job description

NEED ONLY USC/GC. CAN WORK FROM ANY NEARBY OFFICE. NO NEED TO RELOCATE TO A DIFFERENT PLACE

WE ARE LOOKING FOR ARCHITECT FOR THIS POSITION NOT DEVELOPER.

Artificial Intelligence Architect

Java 21+, Spring Boot, Spring AI
Microservices, event-driven architecture (Kafka, SQS/SNS)
REST/GraphQL API design, gRPC
Design patterns, Enterprise architecture and scaling
AI / ML Integration
Experience with Agentic AI / multi-agent frameworks at enterprise scale.
LLM integration via Anthropic Claude API, OpenAI, or AWS Bedrock
RAG architectures, vector databases (OpenSearch, Pinecone, pgvector)
Model serving, inference optimization, prompt engineering
Spring AI, Langgraph, Google ADK, A2A, MCP.
Prompt Engineering, prompt caching, Token optimization.
AWS