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Generative Ai Developer Jobs in Indiana (NOW HIRING)

Info Way Solutions

Gen AI Engineer

Indianapolis, IN · On-site

Info Way Solutions is seeking a Generative AI Engineer to design, develop, and deploy cutting-edge generative models across various domains. The role involves working with large language models and ...

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Generative Ai Developer information

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How much do generative ai developer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for generative ai developer in Indiana is $43.09, according to ZipRecruiter salary data. Most workers in this role earn between $22.40 and $52.16 per hour, depending on experience, location, and employer.

What is a generative AI developer?

A Generative AI Developer is a technology professional who specializes in designing, building, and deploying artificial intelligence systems that can create new content, such as text, images, audio, or code. They work with advanced machine learning models, like generative adversarial networks (GANs) or large language models, to enable computers to produce original outputs. These developers often collaborate with data scientists, researchers, and product teams to integrate AI-generated content into software applications and business solutions.

What are the key skills and qualifications needed to thrive as a generative AI developer?

To thrive as a Generative AI Developer, you need strong programming skills (especially in Python), a deep understanding of machine learning concepts, and an advanced degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and experience with cloud platforms or model deployment tools are typically required. Creative problem-solving, adaptability, and effective collaboration are standout soft skills in this evolving field. These abilities are crucial to design, implement, and refine generative models that solve real-world problems and drive innovation.

What are some common challenges faced by generative AI developers when deploying models in production environments?

Generative AI Developers often encounter challenges such as ensuring model reliability, managing computational resource requirements, and addressing ethical considerations like data bias or content safety. Deploying generative models at scale requires robust monitoring to detect unexpected outputs or model drift, and collaboration with data engineers and product teams to optimize performance. Staying up-to-date with evolving frameworks and best practices is essential, as production environments demand both technical rigor and adaptability to new AI advancements.

What is the difference between Generative Ai Developer vs Machine Learning Engineer?

AspectGenerative Ai DeveloperMachine Learning Engineer
CredentialsBachelor's or higher in CS, AI, or related fields; experience with deep learning frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentDevelops AI models for content creation, chatbots, and creative applicationsBuilds and deploys ML models for various data-driven solutions across industries
Industry UsageTech, entertainment, marketing, and creative sectorsFinance, healthcare, tech, and e-commerce sectors

While both roles involve AI and machine learning, Generative Ai Developers focus on creating models that generate content, such as images or text, whereas Machine Learning Engineers develop broader ML solutions for diverse applications. The roles often overlap but differ mainly in their specific focus areas and use cases.

How to become a generative AI developer?

To become a generative AI developer, you should have a strong foundation in programming languages like Python, experience with machine learning frameworks such as TensorFlow or PyTorch, and knowledge of neural network architectures like transformers. Gaining expertise in natural language processing and deep learning, along with practical experience through projects or internships, is essential. Certifications in AI or data science can also enhance your qualifications.

What are popular job titles related to Generative Ai Developer jobs in Indiana?

For Generative Ai Developer jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Generative Ai Developer jobs in Indiana look for?

The top searched job categories for Generative Ai Developer jobs in Indiana are:

What cities in Indiana are hiring for Generative Ai Developer jobs?

Cities in Indiana with the most Generative Ai Developer job openings:

Generative Ai Developer jobs near you
Infographic showing various Generative Ai Developer job openings in Indiana as of August 2026, with employment types broken down into 79% Full Time, 19% Part Time, and 2% Contract. Highlights an 63% Physical, 5% Hybrid, and 32% Remote job distribution, with an average salary of $89,637 per year, or $43.1 per hour.

Generative AI Engineer

Indianapolis, IN • On-site

Prophecy Technologies
Professional, Scientific, and Technical Services • 11 - 50 employees
Learn more about Prophecy Technologiesexternal

Full-time

Posted 9 days ago

Job description

Role Overview:
Design, engineer, and implement enterprise-scale AI/ML and generative AI solutions for clinical data workflows. This role requires delivering secure, scalable architectures independently while maintaining accountability for project delivery and technical excellence.
Key Responsibilities:
  • Conceive, design, and implement AI solutions; analyze workflows and devise innovative technical approaches.
  • Design secure, scalable architectures for AI/ML, generative AI, and agentic solutions.
  • Design and implement emerging AI technologies such as RAG, agentic workflows, and agent-to-agent communication.
  • Build and deploy predictive analytics and generative AI solutions to production environments.
  • Develop robust data/model pipelines, APIs, and integration layers; establish AI/MLOps best practices.
  • Implement CI/CD, monitoring, and observability for AI/ML systems.
  • Own project scope and delivery accountability.

Required Skills:
  • Cloud Platforms: AWS (SageMaker, EC2, S3, Lambda, RDS, Glue, Athena, DynamoDB, Postgres), Databricks (Platform, Delta Lake, Spark, MLflow, SQL).
  • Programming Languages & ML: Python, PySpark, SQL.
  • DevOps & Infrastructure: Git, CI/CD, Docker, Kubernetes, IaC (Terraform/CloudFormation).
  • AI/Data Technologies: Generative AI frameworks, Large Language Models (LLMs), vector databases, Apache Spark.

Qualifications:
  • Bachelor's degree (BS) in Computer Science, Engineering, Mathematics, Statistics or equivalent professional experience.
  • 5+ years of experience in software, data, or ML engineering.
  • 3+ years of experience deploying ML solutions in production environments.

Preferred Skills:
  • Digital Artificial Intelligence (AI) expertise.

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