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Llm Prompt Engineer Jobs in Indiana (NOW HIRING)

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 ...

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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 ...

New

Senior Software Engineer

Indianapolis, IN · On-site

$117K - $154K/yr

Familiarity with LLM-powered systems, such as: * RAG * Chatbots * Agent workflows * Tool use * Prompt engineering * AI-enabled application development * Strong software engineering fundamentals ...

Engineer Senior

Indianapolis, IN · Hybrid

$99K - $137K/yr

Familiarity with LLM concepts such as prompt engineering, retrieval-augmented generation, embeddings, vector databases, model evaluation, responsible AI, guardrails, and production monitoring is ...

Engineer Senior

Indianapolis, IN · On-site +1

$99K - $137K/yr

Familiarity with LLM concepts such as prompt engineering, retrieval-augmented generation, embeddings, vector databases, model evaluation, responsible AI, guardrails, and production monitoring is ...

Engineer Senior

Indianapolis, IN · On-site

$99K - $137K/yr

Familiarity with LLM concepts such as prompt engineering, retrieval-augmented generation, embeddings, vector databases, model evaluation, responsible AI, guardrails, and production monitoring is ...

Data Engineer IV

Indianapolis, IN · On-site

$69 - $71/hr

Experience with generative AI, including prompt engineering, RAG, LLM APIs, or agent workflows. Familiarity with Git, CI/CD for data pipelines, and infrastructure-as-code. Experience with streaming ...

Design and build LLM-powered applications that help staff work more effectively - including document processing, content generation, and conversational interfaces. * Engineer prompt pipelines with ...

Design and build LLM-powered applications that help staff work more effectively - including document processing, content generation, and conversational interfaces. * Engineer prompt pipelines with ...

Principal AI Engineer

Carmel, IN · On-site

$168K - $193K/yr

Developing and operationalizing LLM-powered solutions (RAG, prompt engineering, agent workflows) to extract insights from structured and unstructured data. * Building scalable infrastructure and ...

Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore ... Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt ...

... prompt engineering, LLM evaluation, and fine-tuning, to develop production-ready applications powered by foundation models - Developing automated evaluation frameworks, including LLM-as-judge ...

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Llm Prompt Engineer information

What are some common challenges faced by LLM Prompt Engineers when designing effective prompts for large language models?

LLM Prompt Engineers often encounter challenges such as ensuring prompts are both clear and unambiguous to elicit accurate model responses, as well as avoiding bias or unintended outputs. Balancing creativity and specificity in prompt design can be tricky, especially when tailoring prompts for diverse user intents or specialized domains. Additionally, prompt engineers must frequently iterate and test their prompts, collaborating closely with data scientists and product teams to continually refine them based on observed model behavior and user feedback.

Which LLM is good for prompt engineering?

For a prompt engineer, large language models like OpenAI's GPT-4, Anthropic's Claude, and Google's PaLM are popular choices due to their advanced capabilities and flexibility. Selecting an LLM depends on factors such as API accessibility, customization options, and the specific application requirements. Familiarity with prompt design and understanding model limitations are essential skills for effective prompt engineering.

What is an LLM Prompt Engineer?

An LLM Prompt Engineer is a professional who specializes in designing, testing, and optimizing prompts for large language models (LLMs) such as GPT-4. Their role involves crafting effective instructions and queries to guide the model's output for specific applications, ensuring accuracy, relevance, and reliability. They may also analyze model behavior, implement prompt-based workflows, and collaborate with developers to integrate LLMs into products or services. The goal is to maximize the performance and efficiency of language models in various real-world contexts.

How much do LLM engineers make?

LLM (Large Language Model) engineers typically earn between $100,000 and $180,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in deep learning and NLP can command higher salaries, often exceeding $200,000. Compensation may also include bonuses and stock options in tech companies.

Are prompt engineers still in demand?

Prompt engineers are currently in demand as organizations seek to optimize AI language models for various applications. The role requires skills in natural language processing, prompt design, and familiarity with large language models, making it a valuable position in AI development teams.

What engineer makes $500,000 a year?

Senior AI engineers, including those working as prompt engineers or machine learning engineers, can earn $500,000 or more annually, especially with extensive experience, specialized skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups focused on artificial intelligence and large language models.

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

To thrive as an LLM Prompt Engineer, you need a deep understanding of natural language processing, prompt engineering strategies, and proficiency in programming languages such as Python, often supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), large language model APIs, and version control systems is typically required. Strong analytical thinking, creativity, and effective communication are crucial soft skills for crafting precise prompts and collaborating with cross-functional teams. These skills ensure the development of effective, ethical, and high-performing AI-powered solutions that meet diverse user needs.

What is the difference between Llm Prompt Engineer vs Data Scientist?

AspectLlm Prompt EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related fields; familiarity with NLP and AI toolsBachelor's or higher in CS, Statistics, or related fields; strong programming and statistical skills
Work EnvironmentAI labs, tech companies, startups focusing on NLP and AI modelsData analysis, modeling, and visualization in various industries like finance, healthcare, tech
Employer & Industry UsagePrimarily in AI development, NLP projects, and machine learning teamsAcross industries for data analysis, predictive modeling, and decision support

While both roles involve working with data and AI, Llm Prompt Engineers focus on designing prompts for language models, whereas Data Scientists analyze data to derive insights. The roles share similar educational backgrounds and work environments but differ in their core tasks and industry applications.

What are popular job titles related to Llm Prompt Engineer jobs in Indiana? For Llm Prompt Engineer jobs in Indiana, the most frequently searched job titles are:
What cities in Indiana are hiring for Llm Prompt Engineer jobs? Cities in Indiana with the most Llm Prompt Engineer job openings:

Senior AI Full Stack Engineer

Onebridge

Indianapolis, IN • On-site

Full-time

Posted 3 days ago

New


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.