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Ai Solutions Engineer Jobs in Indiana (NOW HIRING)

Crowe LLP

Senior AI Engineer

South Bend, IN · On-site +1

$102K - $140K/yr

The role is responsible for producing high-quality, well-architected solutions and setting ... Senior AI Engineer 1 mentors junior engineers, supports cross-team collaboration, and contributes ...

Crowe LLP

Senior AI Engineer

Indianapolis, IN · On-site +1

$99K - $137K/yr

The role is responsible for producing high-quality, well-architected solutions and setting ... Senior AI Engineer 1 mentors junior engineers, supports cross-team collaboration, and contributes ...

MISO

Principal AI Engineer

Carmel, IN · On-site

$168K - $193K/yr

Designing, building, and deploying AI-driven solutions, including ML models, generative AI ... Partnering with data scientists, engineers, and technology teams to integrate AI into real-time and ...

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Showing results 21-40

All JobsAi Solutions Engineer JobsAi Solutions Engineer Jobs in Indiana

Ai Solutions Engineer information

See Indiana salary details

$42.3K

$117.3K

$172.7K

How much do ai solutions engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for ai solutions engineer in Indiana is $117,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,600.00 and $133,700.00 per year, depending on experience, location, and employer.

How does an AI Solutions Engineer typically collaborate with cross-functional teams during a project lifecycle?

AI Solutions Engineers frequently work alongside data scientists, software developers, product managers, and business stakeholders throughout a project's lifecycle. Their role involves translating business requirements into technical AI solutions, integrating models into existing systems, and ensuring seamless deployment. Regular communication and collaboration are essential, as they often lead technical discussions, clarify project goals, and address implementation challenges. This cross-functional teamwork fosters innovation and ensures that AI solutions are practical, scalable, and aligned with business objectives.

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

To thrive as an AI Solutions Engineer, you need a strong background in computer science, machine learning, and data analytics, typically supported by a relevant degree and experience with AI frameworks. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, Azure, or GCP), and proficiency in programming languages like Python are essential, along with certifications in AI or cloud technologies. Excellent problem-solving, communication, and teamwork skills help you translate business needs into technical solutions and collaborate across departments. These competencies ensure effective development, deployment, and integration of AI solutions that drive business value.

What is an AI Solutions Engineer?

AI Solutions Engineers are professionals who design, develop, and implement artificial intelligence-based systems and applications to solve business problems. They bridge the gap between AI research and practical deployment, working closely with data scientists, software engineers, and business stakeholders. Their responsibilities often include creating AI models, integrating them into products or workflows, and ensuring these solutions are scalable, reliable, and aligned with organizational goals.

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

AspectAi Solutions EngineerData Scientist
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI/ML toolsBachelor's or higher in CS, Statistics, or related; strong statistical and programming skills
Work EnvironmentDevelops AI solutions, collaborates with engineering teams, implements models in productionAnalyzes data, builds models, interprets results for insights
Employer & Industry UsageTech companies, AI-focused firms, startupsResearch institutions, tech companies, finance, healthcare

While both roles involve AI and data, Ai Solutions Engineers focus on deploying AI solutions in production environments, working closely with engineering teams. Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their focus on implementation versus analysis.

What are popular job titles related to Ai Solutions Engineer jobs in Indiana? For Ai Solutions Engineer jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Ai Solutions Engineer jobs in Indiana look for? The top searched job categories for Ai Solutions Engineer jobs in Indiana are:
What cities in Indiana are hiring for Ai Solutions Engineer jobs? Cities in Indiana with the most Ai Solutions Engineer job openings:
Ai Solutions Engineer jobs near you
Infographic showing various Ai Solutions Engineer job openings in Indiana as of August 2026, with employment types broken down into 86% Full Time, 8% Part Time, and 6% Contract. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution, with an average salary of $117,312 per year, or $56.4 per hour.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Evansville, IN • Remote

Full-time

Re-posted 16 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