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Ai Integration Engineer Jobs in Indiana (NOW HIRING)

Crowe LLP

Senior AI Engineer

South Bend, IN · On-site +1

$102K - $140K/yr

Senior AI Engineer 1 About Crowe Studio Crowe Studio is a business unit dedicated to helping ... Demonstrated success evaluating and integrating LLM APIs (OpenAI, Azure OpenAI, Gemini); hands-on ...

Crowe LLP

Senior AI Engineer

Indianapolis, IN · On-site +1

$99K - $137K/yr

Senior AI Engineer 1 About Crowe Studio Crowe Studio is a business unit dedicated to helping ... Demonstrated success evaluating and integrating LLM APIs (OpenAI, Azure OpenAI, Gemini); hands-on ...

OPENLANE

AI First Software Engineer

Carmel, IN · On-site

Designing scalable, secure services that power complex workflows and integrate across distributed ... Applying AI tools to reduce repetitive work and increase engineering leverage Who You Will Work ...

OPENLANE

AI First Software Engineer

Carmel, IN

Designing scalable, secure services that power complex workflows and integrate across distributed ... Applying AI tools to reduce repetitive work and increase engineering leverage Who You Will Work ...

Deloitte

AI Security Engineer Manager

Indianapolis, IN · On-site

As a Manager in AI Security Engineering, you will play a critical role in securing the development ... Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role ...

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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 Jul 19, 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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position such as an AI executive, senior machine learning engineer, or AI research director that offers a total compensation package including salary, bonuses, and stock options. These roles usually require advanced skills in AI, deep learning, and data science, along with extensive experience and often involve leadership responsibilities in innovative technology companies.

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 data pipelines to ensure seamless integration, often using programming languages like Python and tools such as cloud services. Their role involves testing, troubleshooting, and optimizing AI components for reliable performance within broader 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 engineer makes 500,000 a year?

Highly experienced AI Integration Engineers working in senior or specialized roles at large technology companies can earn salaries approaching or exceeding $500,000 annually, especially when including bonuses and stock options. Such compensation typically requires advanced skills in machine learning, software development, and cloud platforms, along with extensive industry experience and a strong track record of successful projects.

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 July 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.
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Evansville, IN • On-site

Other

Re-posted 28 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply