ZipRecruiter

Log In

1

Llm Prompt Engineer Jobs (NOW HIRING)

Tata Consultancy Service Limited

Engineer

Irving, TX · On-site

$90K - $100K/yr

Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI. * Basic knowledge of Hybrid prompting technique * Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.

Tata Consultancy Service Limited

Engineer

Jersey City, NJ · On-site

$90K - $100K/yr

Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI. * Basic knowledge of Hybrid prompting technique * Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.

Tata Consultancy Service Limited

Engineer

Irving, TX · On-site

$95K - $105K/yr

Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI. * Basic knowledge of Hybrid prompting technique * Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.

Tata Consultancy Service Limited

iOS Engineer

Irving, TX · On-site

$80K - $100K/yr

Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI. * Basic knowledge of Hybrid prompting technique * Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.

latitude

Applied AI Prompt Engineer

Washington, DC · Hybrid

Applied AI Prompt Engineer DeVry University strives to close our society's opportunity gap and ... Stay up to date on prompting techniques, LLM capabilities, and platform enhancements. * Drive ...

Diverse Lynx

AI ML Engineer

Sunrise, FL · Hybrid

Knowledge of LLM, Prompt Engineering, RAG Architecture, Agentic AI. * Basic knowledge of Hybrid prompting technique * Knowledge in Generative AI tools like LangChain, Hugging Face, Llama Index etc.

Addison Group

AI Developer

The Woodlands, TX · On-site

$100K - $120K/yr

Strong understanding of LLM prompt engineering, embeddings, and foundational Retrieval-Augmented Generation (RAG) concepts. * Proficiency in building microservices and integrating them into complex ...

next page

Showing results 1-20

All JobsLlm Prompt Engineer Jobs

Llm Prompt Engineer information

See salary details

$37

$58

$85

How much do llm prompt engineer jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for llm prompt engineer in the United States is $58.21, according to ZipRecruiter salary data. Most workers in this role earn between $45.43 and $71.15 per hour, depending on experience, location, and employer.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries. Roles involving leadership, technical expertise, or working at major tech companies often have compensation packages reaching or exceeding this level.

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 access, customization options, and the specific application requirements. Familiarity with prompt design and model tuning is essential 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 prompt engineers typically earn between $80,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in AI and machine learning can command higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in tech-focused organizations.

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 like GPT, making it a valuable position in AI development teams.

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.

More about Llm Prompt Engineer jobs
What cities are hiring for Llm Prompt Engineer jobs? Cities with the most Llm Prompt Engineer job openings:
What states have the most Llm Prompt Engineer jobs? States with the most job openings for Llm Prompt Engineer jobs include:
What job categories do people searching Llm Prompt Engineer jobs look for? The top searched job categories for Llm Prompt Engineer jobs are:
Llm Prompt Engineer jobs near you
GenAI Prompt Engineer - Hybrid

GenAI Prompt Engineer - Hybrid

Synersys Technologies

Dallas, TX • Hybrid

Other

Posted 9 days ago

Job description

Hybrid

Role Summary

We are seeking a AI prompt engineer to join an innovative and high-impact team building AI capabilities within enterprise systems for a leading wealth management client. In this role, you will help design and optimize prompt-driven experiences that make AI assistants, automation workflows, and decision-support tools more effective, reliable, and scalable across the business. This is an opportunity to shape the next generation of enterprise AI in a highly visible environment, where innovation, rigor, and business value all matter. You’ll contribute to prompt design, testing, evaluation, optimization and governance while helping establish repeatable patterns for responsible AI use in a regulated financial services setting. The ideal candidate is curious, hands-on, and energized by solving real-world problems at the intersection of AI, enterprise technology, and wealth management

This role partners with product, engineering, UX, data, and domain teams to translate user needs into effective instructions, guardrails, and interaction patterns that drive high-quality model outputs. The position requires strong judgment, experimentation discipline, and a practical understanding of LLM behavior, context management, and evaluation.

Key Responsibilities

Design and refine prompts, prompt chains, and prompt templates for enterprise AI use cases

Develop instructions, examples, guardrails, and system messages to improve response quality and consistency

Test model behavior across scenarios, edge cases, and failure modes

Create and apply evaluation criteria for relevance, accuracy, tone, safety, and task completion

Collaborate with product and engineering teams to embed prompts into production workflows

Analyze user feedback, logs, and output quality to identify prompt improvements

Support retrieval-augmented generation workflows by optimizing context selection and prompt grounding

Establish prompt versioning, testing, documentation, and governance practices

Work with domain experts to encode business logic, policy requirements, and domain terminology

Required Qualifications

Bachelor’s degree in Computer Science, Engineering, Linguistics, Cognitive Science, Information Systems, or related field

6+ years of experience in AI, NLP, conversational design, product writing, software engineering, or related discipline

Hands-on experience designing and testing prompts for LLM-based applications

Strong understanding of prompt patterns, context windows, hallucination risks, and model limitations

Experience with AI evaluation methods, experimentation, and quality measurement

Ability to communicate technical trade-offs to both technical and non-technical stakeholders

Preferred Qualifications

Experience with RAG, vector databases, semantic search, or AI orchestration frameworks

Familiarity with Python, SQL, APIs, or workflow automation

Experience in large enterprise environments, consulting / professional services, regulated, or high-compliance environments

Knowledge of prompt testing tools, observability, or LLMOps practices

Background in UX writing, conversation design, or content strategy

Core Competencies

Precision in language and instruction design

Analytical thinking and experimentation

Cross-functional collaboration

Strong attention to quality and consistency

Comfort with ambiguity and rapidly changing AI capabilities

Practical problem solving with a bias toward measurable outcomes

Apply