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Ai Integration Engineer Jobs in Kansas (NOW HIRING)

Human Agency

This is the engineering role for someone who sees the current AI moment not as hype but as ... Frontend, backend, infrastructure, LLM integration, agent frameworks - you move fluidly between ...

Guida's Dairy

Sr. Systems Engineer - AI

Kansas City, KS · On-site

$100K - $137K/yr

The engineer partners closely with application teams, platform engineering, and IT operations to ... Integrate AI services into enterprise application and infrastructure ecosystems, ensuring ...

RadNet, Inc.

Sr. Systems Engineer - AI

Kansas City, KS · On-site

$98 - $139/hr

The engineer partners closely with application teams, platform engineering, and IT operations to ... Integrate AI services into enterprise application and infrastructure ecosystems, ensuring ...

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All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Kansas

Ai Integration Engineer information

See Kansas salary details

$39.7K

$110.8K

$154.7K

How much do ai integration engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for ai integration engineer in Kansas is $110,835.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,800.00 and $124,900.00 per year, depending on experience, location, and employer.

What are some common challenges faced by AI integration engineers when deploying machine learning models into existing business systems?

AI Integration Engineers often encounter challenges such as ensuring compatibility between machine learning models and legacy systems, managing data privacy and security, and optimizing model performance for real-time applications. They must also address issues related to model scalability and monitoring, as well as facilitate smooth collaboration between data science, IT, and business teams. Overcoming these challenges requires strong problem-solving skills, effective communication, and a deep understanding of both AI technologies and enterprise infrastructure.

What are the key skills and qualifications needed to thrive as an AI integration engineer, and why are they important?

To thrive as an AI Integration Engineer, you need a solid background in computer science, programming (Python, Java, or similar), and experience with AI/ML frameworks, often supported by a bachelor's degree in a related field. Familiarity with cloud platforms (such as AWS, Azure, or Google Cloud), API development, and tools like TensorFlow or PyTorch is typically required. Strong problem-solving abilities, collaboration, and clear communication are essential soft skills for bridging technical and business needs. These competencies ensure successful deployment and seamless integration of AI solutions into existing systems, driving innovation and business value.

What is the difference between Ai Integration Engineer vs Data Scientist?

AspectAi Integration EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; certifications in AI/ML toolsBachelor's or higher in CS, Statistics, or related; advanced degrees common
Work EnvironmentDeveloping and deploying AI solutions, integrating AI APIs into applicationsAnalyzing data, building predictive models, interpreting complex datasets
Employer & Industry UsageTech companies, AI service providers, software firmsResearch institutions, tech companies, finance, healthcare

While both roles involve AI, the Ai Integration Engineer focuses on implementing and integrating AI solutions into applications, whereas the Data Scientist analyzes data to develop models and insights. The roles often overlap but differ mainly in their primary focus: deployment versus analysis.

What is an AI integration engineer?

AI Integration Engineers are professionals who specialize in implementing artificial intelligence solutions into existing systems, products, or workflows. They work closely with data scientists, software developers, and business teams to ensure that AI models and technologies are effectively deployed and seamlessly integrated. Their responsibilities often include customizing AI tools, developing APIs, ensuring data compatibility, and monitoring performance post-integration. These engineers play a crucial role in bridging the gap between AI research and practical business applications.

Are AI Integration Engineers highly paid?

AI Integration Engineers typically earn higher-than-average salaries due to their specialized skills in AI systems, programming, and data analysis. Compensation varies based on experience, location, and industry, but they are generally well-compensated compared to many other engineering roles.
What are popular job titles related to Ai Integration Engineer jobs in Kansas? For Ai Integration Engineer jobs in Kansas, the most frequently searched job titles are:
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Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer job openings in Kansas as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $110,835 per year, or $53.3 per hour.

AI Engineer II - Translation

Propio

Overland Park, KS

Full-time

Re-posted 24 days ago

Propio rating

6.1

Company rating: 6.1 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

367th of 485 rated business services

Job description

Description

Propio is on a mission to make communication accessible to everyone. As a leader in real-time interpretation and multilingual language services, we connect people with the information they need across language, culture, and modality. We're committed to building AI-powered tools to enhance interpreter workflows, automate multilingual insights, and scale communication quality across industries.


We are seeking an AI Engineer II - Translation that will design and optimize machine learning solutions that enhance Propio's translation and localization capabilities, working closely with the translation team and the AI Engineers. This role focuses on developing neural machine translation models optimized for low-resource and specialized languages, improving post-editing workflows, and integrating AI seamlessly with linguist workflows to deliver faster and more accurate translations. 
Key Responsibilities:

  • Design, train, and deploy neural machine translation (NMT) systems for multilingual scenarios, with emphasis on low-diffusion languages. 
  • Optimize models for low-resource and specialized domain languages, leveraging techniques like transfer learning and few-shot adaptation. 
  • Collaborate with the LLM AI Engineer to integrate large language models into translation pipelines and compare approaches for different language pairs. 
  • Develop post-editing and quality assurance tools to augment human translators, incorporating human-in-the-loop feedback. 
  • Work closely with linguists, product managers, and engineers to integrate AI into translation pipelines and gather domain feedback. 
  • Continuously evaluate and benchmark model performance using standardized metrics (BLEU, COMET) and custom domain-specific metrics. 
  • Stay current with research advancements in multilingual NLP and low-resource translation techniques. 


Requirements


Qualifications:

  • Bachelor's or Master's degree in Computer Science, Computational Linguistics, Statistics, or related field.
  • Strong background in NLP and machine translation systems. 
  • Proven experience optimizing models for low-resource or underrepresented languages. 
  • Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face). 
  • Experience with multilingual datasets, translation quality evaluation, and human feedback incorporation. 

Preferred Qualifications:

  • Prior work in translation, interpretation, summarization, or cross-lingual QA
  • Contributions to open-source NLP projects and translation quality projects
  • Experience working with speech-to-text pipelines or multimodal systems

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