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Ai Integration Engineer Jobs in Indiana (NOW HIRING)

First Databank

Advanced Integrations Engineer

Carmel, IN · On-site

$98K - $132K/yr

Lead technical design and code review sessions; establish and reinforce development standards for integration and API services. * Apply AI-assisted engineering practices using coding agents (such as ...

Hearst

Advanced Integrations Engineer

Carmel, IN

$98K - $132K/yr

Lead technical design and code review sessions; establish and reinforce development standards for integration and API services. * Apply AI-assisted engineering practices using coding agents (such as ...

Hearst

Advanced Integrations Engineer

Carmel, IN

$98K - $132K/yr

Lead technical design and code review sessions; establish and reinforce development standards for integration and API services. * Apply AI-assisted engineering practices using coding agents (such as ...

Hearst

Advanced Integrations Engineer

Carmel, IN

$98K - $132K/yr

Lead technical design and code review sessions; establish and reinforce development standards for integration and API services. * Apply AI-assisted engineering practices using coding agents (such as ...

Hearst Health

Advanced Integrations Engineer

Carmel, IN · On-site

$98K - $132K/yr

Lead technical design and code review sessions; establish and reinforce development standards for integration and API services. * Apply AI-assisted engineering practices using coding agents (such as ...

Hearst

Advanced Integrations Engineer

Carmel, IN · On-site

$98K - $132K/yr

Lead technical design and code review sessions; establish and reinforce development standards for integration and API services. * Apply AI-assisted engineering practices using coding agents (such as ...

Deloitte

AI Engineer Consultant

Indianapolis, IN · Hybrid

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

Deloitte

AI Engineer Senior Consultant

Indianapolis, IN · Hybrid

$99K - $137K/yr

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations) and a Lead AI Solutions Architect (end-to-end solution architecture, integration patterns, non ...

Deloitte

Google AI Lead Architect

Indianapolis, IN

$52.75 - $72.50/hr

AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure.

Lasting Change, Inc

AI Engineer

Fort Wayne, IN · On-site

The AI Engineer is Lasting Change's first dedicated AI role, joining an established Data ... Evaluate, select, and integrate best-in-class LLM and AI platform tooling, with preference for ...

Lasting Change Inc

AI Engineer

Fort Wayne, IN · On-site

Description The AI Engineer is Lasting Change's first dedicated AI role, joining an established ... Evaluate, select, and integrate best-in-class LLM and AI platform tooling, with preference for ...

Unisys

Web application Developer

Indianapolis, IN · On-site

... engineer. This role requires a well-rounded full-stack background across modern web technologies ... Integration with LLMs and AI APIs (e.g., Azure OpenAI, AWS Bedrock, or similar platforms)

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All JobsAi Integration Engineer JobsAi Integration Engineer Jobs in Indiana

Ai Integration Engineer information

See Indiana salary details

$42.3K

$118.3K

$165.1K

How much do ai integration engineer jobs pay per year?

As of Jun 25, 2026, the average yearly pay for ai integration engineer in Indiana is $118,256.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,000.00 and $133,200.00 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 does an AI integration engineer do?

An AI integration engineer designs and implements systems that incorporate artificial intelligence into existing software or hardware platforms. They work with machine learning models, APIs, and development tools to ensure seamless integration, often collaborating with data scientists and software developers to optimize AI functionalities within applications.

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.

Are AI engineers highly paid?

AI integration engineers are generally well-paid due to the high demand for expertise in artificial intelligence, machine learning, and data analysis. Salaries vary based on experience, location, and industry, but they tend to be above average compared to many other engineering roles. Advanced skills in programming, neural networks, and cloud platforms can further increase earning potential.

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 engineers make $500,000?

Senior engineers in specialized fields such as software, AI, or data engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and leadership roles. High compensation often includes bonuses, stock options, or profit sharing, particularly in tech companies or startups.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles such as AI executives, senior machine learning engineers, or specialized AI consultants earning this level of compensation. These positions often require advanced skills in AI development, leadership experience, and may include bonuses or stock options that contribute to total compensation.

What are AI Integration Engineers?

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.
What are popular job titles related to Ai Integration Engineer jobs in Indiana? For Ai Integration Engineer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Ai Integration Engineer jobs in Indiana look for? The top searched job categories for Ai Integration Engineer jobs in Indiana are:
What cities in Indiana are hiring for Ai Integration Engineer jobs? Cities in Indiana with the most Ai Integration Engineer job openings:
Ai Integration Engineer jobs near you
Infographic showing various Ai Integration Engineer job openings in Indiana as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $118,256 per year, or $56.9 per hour.

AI Integration Consultant

Meraki7 Inc

Indianapolis, IN • On-site

Other

Posted 10 days ago

Job description

Role Focus: AI Integration Consultant – Research Labs / Learning & Development
Duration: 18 Months Contract

Location : Indianapolis
 

Key Responsibilities

1. Process & Workflow Automation

  • Develop and maintain automated workflows using ServiceNow, Power Automate, and Smartsheet to support learning processes.
  • Design and build ServiceNow catalog items, workflows, and service portal solutions for Research Laboratories L&D service requests.
  • Own and maintain current workflow solutions and SharePoint lists.
  • Monitor and manage the RL L&D technology request form, including triaging and responding to incoming requests.
  • Collaborate with internal automation teams to develop, optimize, and improve workflow solutions.

2. AI Solutions Development

  • Develop AI-powered solutions to improve L&D processes using Microsoft Copilot, Copilot Studio, Copilot Agents, Claude, Claude Code, or similar tools.
  • Create Copilot Agents and custom AI assistants to support L&D operations and learner experiences.
  • Use Claude and Claude Code for development automation and process improvement.
  • Recommend and implement AI tools to improve content generation, data analysis, learner support, and operational efficiency.
  • Stay updated on emerging AI technologies and provide recommendations for adoption.

3. Technology Implementation & Learning Technology Support

  • Support Learning Process and Technology team members with key initiatives and technology tool development.
  • Consult with L&D stakeholders on the best technology solutions to improve efficiency.
  • Provide project support and technical expertise for learning technology implementations.
  • Drive the development and delivery of technology solutions in collaboration with the RL L&D team.
  • Support LMS administration and reporting needs, preferably with SAP SuccessFactors Learning.

4. Cross-Functional Collaboration

  • Work closely with the Technology Lead and Data Metrics Strategy Lead to align technology solutions with organizational priorities.
  • Collaborate with other Learning & Development groups to implement shared technology solutions.
  • Partner with enterprise technology teams and IT to ensure alignment with corporate standards and infrastructure.
  • Provide consultation on learning technology projects and implementation best practices.

5. Web Server & Content Management

  • Manage and maintain content on RL L&D web servers in compliance with client policies.
  • Support the RL L&D learning content server and related infrastructure.
  • Ensure web content meets accessibility, security, and organizational standards.

6. Document, Knowledge & Data Management

  • Support document and knowledge management initiatives within RL L&D.
  • Develop and maintain SharePoint sites and knowledge repositories for performance support materials.
  • Consult with business partners on knowledge management best practices and solutions.
  • Support data management practices to ensure information accuracy, accessibility, and usability.

Minimum Qualifications

  • Bachelor’s degree or higher in Technology Management, Information Systems, Computer Science, or a related field.
  • 3+ years of hands-on experience with process automation tools such as ServiceNow, Power Automate, and Smartsheet.
  • Experience developing ServiceNow catalogs, workflows, and service portal solutions.
  • Proven experience with Microsoft Power Platform, especially Power Automate and Power Apps.
  • Experience with web server management and content administration.
  • Demonstrated ability to scope, lead, and deliver technology projects.
  • Experience implementing or supporting learning technology projects.

Must-Have Skills

  • 3+ years of hands-on experience with ServiceNow, Power Automate, and Smartsheet for process and workflow automation.
  • Strong ServiceNow development experience, including catalog items, workflows, and service portal solutions.
  • Proven expertise with Microsoft Power Platform, particularly Power Automate and Power Apps.
  • Experience implementing and supporting learning technology solutions, ideally LMS platforms such as SAP SuccessFactors Learning.
  • Experience developing AI-enabled solutions using Microsoft Copilot, Copilot Studio, Copilot Agents, Claude, Claude Code, or similar AI technologies.
  • Bachelor’s degree or higher in Technology Management, Information Systems, Computer Science, or related programs.

Nice-to-Have Skills

  • Pharmaceutical or life sciences industry experience.
  • CRO industry experience.
  • SharePoint administration and development experience.
  • Web server and content management experience.
  • Programming skills in JavaScript, Python, SQL, JSON, HTML, or CSS.
  • SuccessFactors Learning administration and reporting experience.
  • Working knowledge of regulated pharmaceutical environments.
  • Experience managing multiple projects simultaneously.
  • Strong problem-solving and stakeholder management skills.
  • Ability to influence without authority.
  • Strong communication skills and ability to build trust with internal and external partners.

Target Candidate Background

Ideal candidates may come from:

  • Pharmaceutical companies
  • Life sciences companies
  • CROs
  • Regulated technology environments
  • L&D technology teams
  • ServiceNow / Power Platform automation teams
  • Learning technology implementation teams

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