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Data Engineer With Jobs in Kansas (NOW HIRING)

Conflux Systems

Lead AI Engineer

Kansas City, KS · On-site

$98K - $130K/yr

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 ...

Moore

Data Programmer

Topeka, KS · On-site

The Data Programmer role involves working with large datasets to analyze, plan, and execute complex processing workflows, focusing on creating end-to-end solutions for data transformations and large ...

Accenture

Google Data Specialist

Overland Park, KS · On-site

$70K - $196K/yr

You Are A hands-on Specialist with foundational experience in Data Engineering, Analytics, or Machine Learning-now building deep expertise in Google Cloud Platform (GCP). You are eager to apply ...

SolvdUS, Inc

Director of Data Engineering

Lenexa, KS · On-site +1

Director of Data Engineering We are seeking an experienced Director of Data Engineering responsible ... The role requires strong experience with AWS-based data architectures, infrastructure automation ...

Finite State

Participate in product discovery and help shape roadmaps with a strong technical and data-informed ... Security-Integrated DevOps: Support automated testing, CI/CD pipelines, database migrations, and ...

Cloudera

Engineering Seniority Level: Mid-Senior level At Cloudera, we empower people to transform complex ... With as much data under management as the hyperscalers, we're the preferred data partner for the ...

Finite State

Participate in product discovery and help shape roadmaps with a strong technical and data-informed ... Security-Integrated DevOps: Support automated testing, CI/CD pipelines, database migrations, and ...

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What is the difference between Data Engineer With vs Data Scientist?

AspectData Engineer WithData Scientist
Required CredentialsBachelor's in CS, Engineering, or related field; certifications like AWS, GCP, or AzureBachelor's or higher in CS, Statistics, or related; often with certifications in data analysis or machine learning
Work EnvironmentBuild and maintain data pipelines, databases, and infrastructureAnalyze data, develop models, and generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data infrastructure is criticalResearch institutions, tech firms, marketing, and analytics-focused companies

While Data Engineers With focus on developing and maintaining data infrastructure, Data Scientists analyze data to derive insights. Both roles often collaborate but serve different functions within data teams.

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Infographic showing various Data Engineer With job openings in Kansas as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Lead AI Engineer

Conflux Systems

Kansas City, KS • On-site

$98K - $130K/yr

Full-time

Re-posted 21 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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