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Llm Prompt Engineer Jobs in Indiana (NOW HIRING)

BC Forward

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 ...

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 · 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 ...

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 · Remote

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 ...

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 ...

Salesforce, Inc.

AI Solution Orchestrator

Indianapolis, IN · On-site

$52.75 - $68/hr

Apply established prompt engineering techniques (chain-of-thought, few-shot, role prompting ... of LLM Limitations: Understand and proactively account for model limitations such as token ...

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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 job categories do people searching Llm Prompt Engineer jobs in Indiana look for? The top searched job categories for Llm Prompt Engineer jobs in Indiana are:
What cities in Indiana are hiring for Llm Prompt Engineer jobs? Cities in Indiana with the most Llm Prompt Engineer job openings:
Llm Prompt Engineer jobs near you
Trust & Safety Engineer (GenAI) - Remote

Trust & Safety Engineer (GenAI) - Remote

micro1 AI

Indianapolis, IN • Remote

$50 - $90/hr

Part-time

Posted 14 days ago

Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert


Role Type: Contractor


Location: Remote


micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
  2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
  3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
  4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
  5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
  6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.


Preferred Qualifications

  1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
  2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
  3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
  4. High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations.
  5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
  6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
  7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.

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