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Ai Integration Engineer Jobs in Indiana (NOW HIRING)

Deloitte

System Integration Engineer

Indianapolis, IN · On-site

$159.60K/yr

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

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

$99.90K - $137.20K/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

AI Engineer Senior Consultant

Indianapolis, IN · Hybrid

$99.90K - $137.20K/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

AI Data Engineer - Senior Consultant

Indianapolis, IN · Hybrid

$99.90K - $137.20K/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 ...

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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 May 29, 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 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 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 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 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.

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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 May 2026, with employment types broken down into 7% Internship, 86% Full Time, and 7% Contract. Highlights an 86% In-person, 7% Hybrid, and 7% Remote job distribution, with an average salary of $118,256 per year, or $56.9 per hour.
LLM Integration Engineer (Remote)

LLM Integration Engineer (Remote)

Outlier AI

Indianapolis, IN • Remote

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

About the Project

Outlier helps the world’s most innovative companies improve their AI agents by providing human feedback. Do you want to shape the future of autonomous agents like OpenClaw?

We collaborate with leading AI organizations to train Large Language Models (LLMs) to function as proactive, multi-step agents. Our projects focus on teaching these systems how to design, coordinate, and optimize complex, real-world architectural workflows.

Whether you are a passionate orchestration guru or experienced software developer — we want you to help us train the world's most advanced generative systems.

Ideal Qualifications

  • 2+ years of experience in backend engineering, AI automation, or complex systems integration.
  • Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting).
  • Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases.
  • Practical experience building for live, non-mocked environments and handling multi-turn system interactions.
  • Outstanding attention to detail and the ability to provide clear, high-density technical feedback on complex system behaviors.

Nice to have

  • Expertise building multi-stage coordination tasks where data acquisition leads to reasoned output.
  • Hands-on experience integrating agents with live tools such as Supabase, Gmail, and various APIs to solve real-world problems.
  • High level of comfort implementing persistent state and session discovery using MEMORY.md to track agent progress.
  • Experience identifying subtle failures like privacy leaks, authority escalation, or indirect prompt injections.

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