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Senior Generative Ai Engineer Jobs in Indiana (NOW HIRING)

Elevance Health

Gen AI Engineer

Indianapolis, IN · Hybrid

Gen AI Engineer Gen AI Engineer Location: This role requires associates to be in-office 1 - 2 days ... Experience with NLP, LLMs (extractive and generative), fine-tuning and LLM model development.

Elevance Health

Gen AI Engineer

Indianapolis, IN · Hybrid

Gen AI Engineer Location: This role requires associates to be in-office 1 - 2 days per week ... Experience with NLP, LLMs (extractive and generative), fine-tuning and LLM model development.

Precinmac

AI Engineer

Indianapolis, IN · On-site

The AI Engineer is an experienced technical professional who bridges business strategy with AI ... Experience with Generative AI, AI Agents, or Reinforcement Learning * Python proficiency and ...

Deloitte

Senior AI Engineer - SFL Scientific

Indianapolis, IN · On-site

$99K - $137K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Pwc

AI Engineer

Indianapolis, IN · On-site

$55K - $187K/yr

... AI Engineer, you will be at the forefront of transforming raw data into actionable insights ... As a Senior Associate, you will leverage your skills to analyze complex problems, mentor others ...

SEP

AI Engineer (in person)

Westfield, IN

SEP has an opening for a software engineer with a focus in Artificial Intelligence (Generative AI, Computer Vision, or Natural Language Processing). We need your expertise to expand the AI services ...

SEP

AI Engineer (in person)

Westfield, IN · On-site

SEP has an opening for a software engineer with a focus in Artificial Intelligence (Generative AI, Computer Vision, or Natural Language Processing). We need your expertise to expand the AI services ...

SEP

AI Engineer (in person)

Westfield, IN · On-site

SEP has an opening for a software engineer with a focus in Artificial Intelligence (Generative AI, Computer Vision, or Natural Language Processing). We need your expertise to expand the AI services ...

Autodesk

$84K - $111K/yr

Job Requisition ID # 26WD99820 Position Overview Autodesk is seeking a Senior Cloud & AI FinOps ... As generative AI tools become deeply embedded in our engineering and corporate workflows, you will ...

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Senior Generative Ai Engineer information

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 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 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 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.
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Senior Generative Ai Engineer jobs near you

Senior AI Full Stack Engineer

Onebridge

Indianapolis, IN • On-site, Remote

Full-time

Posted 11 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 Full Stack Engineer to join our innovative and dynamic team.
Senior AI Full Stack Engineer | About You
As a Senior AI Full Stack Engineer, 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 Full Stack Engineer | 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 Full Stack Engineer | 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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