1

Ai Implementation Jobs in Kansas (NOW HIRING)

Sr. Systems Engineer - AI

Kansas City, KS ยท On-site

$100K - $137K/yr

Implement and maintain monitoring, logging, and alerting aligned to enterprise ITOM practices * Define and track service health, performance, and data quality metrics for AI-enabled services

Sr. Systems Engineer - AI

Kansas City, KS ยท On-site

$98 - $139/hr

Implement and maintain monitoring, logging, and alerting aligned to enterprise ITOM practices * Define and track service health, performance, and data quality metrics for AI-enabled services

New

From advisory and tooling to implementation and education, we meet clients where they are and help them integrate AI in ways that align with their mission and values. Our goal is to empower teams to ...

From advisory and tooling to implementation and education, we meet clients where they are and help them integrate AI in ways that align with their mission and values. Our goal is to empower teams to ...

Support the security team in implementing data protection and acceptable use guardrails for AI within 3 months * At least one AI pilot deployed in production with measurable results within 6 months

Experience leading and implementing AI transformation initiatives. Has personally led the deployment of at least one AI/ML system into production at a company that uses it daily.Bachelor's degree in ...

Senior AI Engineer

Toronto, KS ยท On-site

$88.09 - $117.45/hr

Architect and implement AI-powered features end-to-end, from model integration and prompt engineering to deployment, monitoring, and iteration * Integrate LLM APIs, ML models, and intelligent ...

Lead AI / ML Engineer

Overland Park, KS ยท On-site

$101K - $133K/yr

Developing and implementing AI models and solutions, focusing on ethical and responsible practices. * Detecting, evaluating and applying relevant RAI dimensions (bias, fairness, robustness ...

$59K - $81K/yr

From advisory and tooling to implementation and education, we meet clients where they are and help them integrate AI in ways that align with their mission and values. Our goal is to empower teams to ...

Design and implement business logic close to the data using Postgres functions, views, triggers ... AI-Accelerated Development: Treat tools like Cursor, Devin, GitHub Copilot, and agent frameworks as ...

Senior Software Engineer

Leawood, KS ยท On-site

$100 - $130/hr

... implementation. If you're driven to strengthen U.S. defense readiness and protect national interests, Torch.AI offers meaningful impact at national scale. What Makes Torch.AI Different Torch.AI was ...

Showing results 41-60

Ai Implementation information

How to get into AI implementation?

To pursue a career in AI implementation, develop strong skills in programming languages such as Python, understand machine learning frameworks like TensorFlow or PyTorch, and gain experience with data analysis and model deployment. Earning relevant certifications or degrees in computer science, data science, or AI can also enhance your qualifications.

What are the key skills and qualifications needed to thrive in the AI implementation position?

To excel in AI Implementation, you need a robust understanding of machine learning concepts, data analysis, and software development, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, cloud platforms (AWS, Azure), and AI integration frameworks is commonly required, along with relevant certifications. Strong project management, problem-solving abilities, and excellent communication skills are crucial for coordinating with stakeholders and driving adoption. Mastering both technical and interpersonal skills ensures projects are delivered effectively and meet business objectives within diverse organizational settings.

What is an AI implementation?

An AI Implementation job involves deploying artificial intelligence solutions within an organization to improve efficiency, automation, and decision-making. Professionals in this role work closely with data scientists, engineers, and business teams to integrate AI models into existing systems. They manage data pipelines, ensure model performance, and address challenges related to scalability and compliance. Strong technical skills, project management, and an understanding of business processes are essential for success in this role.

What kinds of teams and departments does an AI implementation professional typically collaborate with?

AI Implementation professionals usually work cross-functionally, interacting with data scientists, software engineers, IT departments, and business stakeholders to ensure AI solutions address specific business needs. Regular collaboration with product managers and operations teams helps align technical efforts with strategic objectives and regulatory requirements. You may also work closely with end users to gather feedback, refine implementations, and ensure a smooth adoption process. This collaborative environment not only enhances the quality of AI deployments but also offers valuable exposure to different aspects of the organization, fostering professional growth.

How to become an AI implementation specialist?

To become an AI implementation specialist, individuals typically need a strong background in computer science, data science, or related fields, along with knowledge of AI and machine learning algorithms. Gaining experience with programming languages like Python, familiarity with AI frameworks such as TensorFlow or PyTorch, and understanding of deployment environments are essential. Certifications in AI or cloud platforms can also enhance job prospects in this role.
What are popular job titles related to Ai Implementation jobs in Kansas? For Ai Implementation jobs in Kansas, the most frequently searched job titles are:
What cities in Kansas are hiring for Ai Implementation jobs? Cities in Kansas with the most Ai Implementation job openings:
Infographic showing various Ai Implementation job openings in Kansas as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Sr. Systems Engineer - AI

Guida's Dairy

Kansas City, KS โ€ข On-site

$100K - $137K/yr

Full-time

Posted 4 days ago


Job description

Serve as a senior-level technical leader within IT Solutions Delivery, responsible for deploying, operating, and continuously improving production AI-enabled platforms and services that support critical business applications.

This role ensures that AI/ML capabilities are delivered into production environments using the same operational rigor, reliability standards, and support models as enterprise IT infrastructure, enabling consistent uptime, performance, and scalability. The engineer partners closely with application teams, platform engineering, and IT operations to ensure AI services are production-ready, supportable, and aligned to enterprise operational standards.

Job Duties and Responsibilities:

  • Deploy AI/ML solutions into enterprise production environments using repeatable, low-risk release processes
  • Build and maintain automated pipelines that support solution delivery across development, testing, and production
  • Ensure all AI services meet enterprise standards for deployment, configuration, and change management
  • Own day-to-day operations of AI-enabled platforms, ensuring availability, reliability, and performance of business-facing services
  • Establish and enforce site reliability engineering (SRE) practices, including high availability and fault tolerance, capacity planning and auto-scaling, and redundancy and failover strategies
  • Continuously optimize platform performance, resource utilization, and cost efficiency
  • Implement and maintain monitoring, logging, and alerting aligned to enterprise ITOM practices
  • Define and track service health, performance, and data quality metrics for AI-enabled services
  • Configure proactive alerting for degradations or anomalies and integrate with enterprise event management platforms
  • Develop and maintain operational dashboards and visibility tools for ongoing service assurance
  • Provide production support for AI-enabled services, including incident triage and resolution, performing root cause analysis (RCA), and implementing corrective and preventative actions
  • Develop and maintain runbooks and support procedures to enable consistent issue resolution
  • Partner with operations and service desk teams to ensure support readiness and knowledge transfer
  • Integrate AI services into enterprise application and infrastructure ecosystems, ensuring compatibility with existing platforms
  • Collaborate with solution delivery, infrastructure, and application teams to ensure services are fully operationalized, properly monitored, and supportable through standard IT processes
  • Ensure AI components behave as first-class enterprise services within the broader application landscape
  • Ensure all AI services are deployed and operated in alignment with enterprise security, compliance, and data protection standards
  • Manage the full operational lifecycle of AI-enabled services, including versioning and controlled releases, performance tuning and optimization, and continuous improvement of deployment and support processes
  • Identify opportunities to automate and standardize platform operations to improve efficiency and reliability
  • Serve as a subject matter expert in AI platform operations
  • Lead or support resolution of major incidents and complex operational challenges
  • Drive adoption of standardized operational practices, including runbooks, and reliability engineering
  • Provide guidance to project teams to ensure solutions are designed for production support from day one

Education and Experience

  • Undergraduate degree in computer science, information technology, or related curriculum (or equivalent combination of experience and education)
  • 8 or more years of information technology, cloud or platform engineering, DevOps, site reliability engineering (SRE), infrastructure engineering, application operations, or related experience that includes experience:
    • supporting AI/ML platforms, machine learning operations (MLOps), AI-enabled applications, large-scale data platforms, or other advanced analytics environments in production
    • deploying, monitoring, and supporting business-critical applications in cloud-based and hybrid enterprise environments
    • designing and managing CI/CD pipelines, automated deployment processes, and infrastructure-as-code solutions
    • partnering with application development, infrastructure, security, and operations teams to operationalize new technologies and services
    • serving as a technical lead, senior engineer, or escalation point for complex production issues
  • Certification and/or License - may be required during course of employment

Knowledge, Skills, and Abilities

  • Deep understanding of managing supported systems in a large-scale environment
  • Solid understanding of AI/ML operational practices, including model deployment, model monitoring, inference services, version management, and AI platform lifecycle management
  • Strong understanding of backup technologies and cloud technologies
  • Strong scripting and automation skills
  • Strong collaboration skills with application development, platform engineering, cybersecurity, infrastructure, and service desk teams
  • Strong problem solving and analytical skills with the ability to quickly isolate problems, collect data, establish facts, and draw valid conclusions; able to perform root cause analysis and implement sustainable corrective and preventive actions
  • Able to deploy and maintain highly available, scalable, and supportable AI-enabled services in production environments
  • Able to automate operational processes, platform provisioning, deployments, monitoring, and recovery activities
  • Able to serve as the senior technical escalation point for critical incidents and complex operational challenges
  • Able to influence teams and drive adoption of enterprise operational standards and best practices
  • Able to communicate complex technical concepts to both technical and non-technical stakeholders
  • Able to prioritize multiple operational demands in fast-paced production environments
  • Able to work independently with limited direction while maintaining accountability for enterprise-critical service
  • Must be able to read, write and speak English

An Equal Opportunity Employer including Disabled/Veterans