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Llm Prompt Engineer Jobs in Indiana (NOW HIRING)

Onebridge

Senior AI Full Stack Engineer

Indianapolis, IN · On-site

$120 - $180/hr

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 ...

Deloitte

AI Engineer Consultant

Indianapolis, IN · Hybrid

We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ... prompt/context patterns. * Implement LLM application patterns including RAG, document ingestion ...

Lasting Change, Inc

AI Engineer

Fort Wayne, IN · On-site

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

Lasting Change Inc

AI Engineer

Fort Wayne, IN

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

MISO

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 ...

Kobie Marketing

AI Engineer

Indianapolis, IN · On-site

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 ...

Pwc

AI Engineer

Indianapolis, IN · On-site

$50K - $112K/yr

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

inKind

Data Engineer

Austin, IN · On-site

$135K - $155K/yr

Proficiency in Python and modern AI/ML tooling and experience integrating with LLM APIs (Anthropic ... prompt injection and data leakage to third-party AI services) Benefits & Perks at inKind At inKind ...

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Llm Prompt Engineer information

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.

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

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 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.

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.

Are AI prompt engineers in demand?

AI prompt engineers are increasingly in demand as organizations seek to optimize interactions with large language models and AI systems. The role requires skills in natural language processing, prompt design, and familiarity with AI tools, with job growth driven by expanding AI applications across industries.

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Llm Prompt Engineer jobs near you

Senior AI Engineer - Bioinformatics

Marlabs

Indianapolis, IN • On-site

Full-time

Re-posted 3 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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