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Langgraph Jobs in Kansas (NOW HIRING)

Conflux Systems

Lead AI Engineer

Kansas City, KS · On-site

$98K - $130K/yr

Familiarity with LangChain, LangGraph, vector databases, and Retrieval-Augmented Generation (RAG) pipelines. DevOps & Observability: Strong understanding of CI/CD pipelines, monitoring, logging, and ...

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Langgraph information

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 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 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 popular job titles related to Langgraph jobs in Kansas? For Langgraph jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Langgraph jobs in Kansas look for? The top searched job categories for Langgraph jobs in Kansas are:
What cities in Kansas are hiring for Langgraph jobs? Cities in Kansas with the most Langgraph job openings:
Langgraph jobs near you
Infographic showing various Langgraph job openings in Kansas as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution.
Lead AI Engineer

Lead AI Engineer

Conflux Systems

Kansas City, KS • On-site

$98K - $130K/yr

Full-time

Re-posted 2 days ago

Job description

Title: Lead Data Engineer (with AI. ML, Python, Java, Kafka)
Location: Leawood, KS
Description
  • Led App Development teams and are aware of working with distributed systems
  • Are well aware of architecture (backend) and integrations
  • Taking Applications to production (so awareness of end to end working of systems)
  • Preferably know Kafka
  • Preferably worked as Data Engineering Leads
  • Are tech savvy, have tried out building Gen AI apps.

Role Overview
  • Ascend Learning is seeking a Lead AI Engineer (Contract) who is a driver, not an order taker - someone who leads from the front, manages delivery across the AI team, and ensures successful execution of complex, high-impact AI initiatives.
  • You will architect and deliver applied AI solutions powered by Large Language Models (LLMs) and Small Language Models (SMLs) within a distributed, production-grade ecosystem.
  • This is a hands-on technical leadership and delivery management role that combines engineering excellence, team guidance, and cross-functional collaboration. You will work closely with Technical Product Owners (TPOs), Technical Program Managers (TPMs), Platform Engineering, and Senior Managers to deliver scalable, reliable, and innovative AI applications that transform digital learning experiences.

Roles and Responsibilities
Delivery Management & Leadership: Manage delivery of AI engineering initiatives, ensuring projects are executed on time, within scope, and to high quality standards. Coordinate engineers and workstreams, resolve dependencies, and drive accountability.
Technical Leadership & Team Guidance: Lead and mentor AI engineers in architecture, design, and implementation of best practices. Set engineering standards for quality, reliability, and maintainability.
AI Solution Design & Development: Architect and develop Agentic AI applications using LLMs and SMLs for automation, reasoning, and content generation. Build distributed backend systems with Python, Fast API, Azure, Kafka, and Kubernetes.
Cross-Functional Collaboration: Partner with Technical Product Owners, Technical Program Managers, and Platform Engineering to define scope, success metrics, and optimize infrastructure and performance.
Innovation & Strategic Thinking: Stay current on advancements in LLMs, SMLs, RAG, and Agentic AI frameworks. Experiment with OpenAI and Azure AI tools and promote technical innovation balanced with predictable delivery.
Productionization & Lifecycle Management: Lead productionization of AI application, ensuring reliability, observability, and lifecycle management of deployed solutions.
Qualifications
Education & Experience: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a closely related field-or equivalent practical experience. Minimum of 7 years in software or AI engineering, with at least 2 years in technical leadership or architectural roles, demonstrating a proven track record of delivering complex solutions.
Delivery Management Expertise: Demonstrated success managing end-to-end delivery for engineering teams or overseeing multi-stream technical projects, ensuring timely execution, high standards, and effective coordination across stakeholders.
Technical Proficiency: Deep expertise in designing and implementing distributed systems, microservices architectures, and event-driven solutions. Hands-on experience with production-grade AI systems leveraging Large Language Models (LLMs) and Small Language Models (SMLs).
Technology Stack Mastery: Advanced proficiency in Python, FastAPI, and Azure Cloud. Skilled in deploying and orchestrating solutions with Docker and Kubernetes. Familiarity with LangChain, LangGraph, vector databases, and Retrieval-Augmented Generation (RAG) pipelines.
DevOps & Observability: Strong understanding of CI/CD pipelines, monitoring, logging, and tracing using tools like Datadog. Experienced with modern DevOps best practices to ensure system reliability and maintainability.
Additional Competencies: Working knowledge of OpenAI APIs and the Azure ecosystem, including Cosmos DB, AI Search, and Cognitive Services. Familiarity with front-end frameworks (Angular, React) and principles of UI/UX design, enabling seamless integration of intelligent backends with web applications. Exceptional communication, collaboration, and leadership abilities, with a passion for mentoring teams and driving impactful results.

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