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Senior Generative Ai Engineer 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 ...

Pwc

AI Engineer

Indianapolis, IN

$50K - $112K/yr

... generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models - Developing automated evaluation ...

Major Tool & Machine

AI Engineer

Indianapolis, IN · On-site

Position Title: AI Engineer Position Summary: The AI Engineer is an experienced technical ... Experience with Generative AI, AI Agents, or Reinforcement Learning * Python proficiency and ...

Precinmac

AI Engineer

Indianapolis, IN · On-site

Position Title: AI Engineer Position Summary: The AI Engineer is an experienced technical ... Experience with Generative AI, AI Agents, or Reinforcement Learning * Python proficiency and ...

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Senior Generative Ai Engineer information

What does a senior generative AI engineer do?

A Senior Generative AI Engineer designs, develops, and implements advanced artificial intelligence models, particularly those focused on generating content such as text, images, or audio. They work with large datasets, build and fine-tune generative models like GPT or diffusion models, and oversee the deployment of these systems into production environments. Additionally, they collaborate with cross-functional teams to integrate AI capabilities into products, optimize model performance, and ensure ethical AI practices are followed.

What are the key skills and qualifications needed to thrive as a senior generative AI engineer, and why are they important?

To thrive as a Senior Generative AI Engineer, you need deep expertise in machine learning, deep learning, and natural language processing, typically backed by an advanced degree in computer science or related fields. Proficiency in frameworks like TensorFlow or PyTorch, experience with cloud platforms (e.g., AWS, Azure), and familiarity with large language models are essential, along with relevant certifications. Strong problem-solving skills, creativity, and effective communication set standout engineers apart in this role. These skills and qualities are crucial for designing innovative AI solutions, collaborating across teams, and advancing the capabilities of generative models in real-world applications.

What are some of the unique challenges senior generative AI engineers face when deploying models in production environments?

Senior Generative AI Engineers often encounter challenges such as ensuring model reliability, addressing biases in generated outputs, and managing the significant computational resources required for deployment. There's also a strong need to collaborate with cross-functional teams, including data engineers, product managers, and domain experts, to ensure the solutions align with business goals and maintain user trust. Balancing innovation with ethical considerations and scalability is crucial in this fast-evolving field.

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

AspectSenior Generative Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with generative modelsBachelor's/Master's in CS, Data Science, or related; strong ML fundamentals
Work EnvironmentResearch and development focused, often in AI startups or tech companiesData analysis, model development, often across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech, finance, healthcare, and other sectors utilizing ML solutions

The main difference is that Senior Generative Ai Engineers specialize in developing and optimizing generative models like GPT or GANs, focusing on AI creativity and content generation. Machine Learning Engineers have a broader scope, working on various ML algorithms and applications across multiple industries. Both roles require strong technical skills, but the Senior Generative Ai Engineer's expertise is more specialized in generative AI technologies.

What are the most commonly searched types of Generative Ai Engineer jobs in Indiana?

The most popular types of Generative Ai Engineer jobs in Indiana are:

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

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

What cities in Indiana are hiring for Senior Generative Ai Engineer jobs?

Cities in Indiana with the most Senior Generative Ai Engineer job openings:

Senior Generative Ai Engineer jobs near you

Senior AI Engineer - Bioinformatics

Marlabs

Indianapolis, IN • On-site

Full-time

Re-posted 7 days ago

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Senior AI Engineer - Bioinformatics to join our innovative and dynamic team.
Senior AI Engineer - Bioinformatics | About You
As a Senior AI Engineer - Bioinformatics, you are responsible for building modern, data-driven web applications that enable scientists and researchers to interact with complex datasets intuitively and efficiently. You enjoy working across the entire stack, from designing backend services and APIs to crafting responsive, elegant frontends. You thrive in environments where you collaborate closely with UX designers, scientists, and engineering partners to turn ideas into high-impact tools. You value clean architecture, reusable components, automated testing, and strong engineering best practices. You are energized by creating user experiences that simplify scientific workflows and make large-scale data accessible and actionable.
Senior AI Engineer - Bioinformatics | Day-to-Day
  • Design, develop, and support scalable full-stack applications and AI-powered solutions using Python and modern development technologies.
  • Build and integrate Generative AI capabilities using LLM platforms such as OpenAI, Azure OpenAI, and Anthropic, including prompt engineering and context management.
  • Develop agentic workflows, tool integrations, and function-calling capabilities to automate complex business processes and enhance user experiences.
  • Integrate enterprise applications with platforms such as Microsoft 365, SharePoint, Microsoft Graph, ServiceNow, Jira, and Confluence through secure APIs.
  • Implement secure authentication, authorization, and secrets management practices while ensuring compliance with enterprise security standards.
  • Collaborate with cross-functional teams to deliver, deploy, and continuously improve applications through CI/CD pipelines, containerization, and modern DevOps practices.

Senior AI Engineer - Bioinformatics | Skills & Experience
  • 7+ years of experience in full-stack application development within enterprise or technology-driven environments, with strong proficiency in Python.
  • Hands-on experience building AI and Generative AI solutions, including LLM API integrations, prompt engineering, token management, and conversational AI applications.
  • Strong experience with enterprise integrations, including Microsoft 365, Microsoft Graph, SharePoint, ServiceNow, Jira, Confluence, and REST APIs.
  • Expertise in secure application development, including SSO integrations (SAML, OAuth2, OIDC), API gateways, middleware, and secrets management best practices.
  • Experience with modern DevOps and cloud-native development, including containerization, CI/CD pipelines, deployment automation, and application lifecycle management.

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