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Text Prompt Engineering Jobs (NOW HIRING)

Experience in prompt engineering, data preprocessing, model fine-tuning, and evaluation. Experience ... Experience with large language models (LLMs), text generation, and image gen. Strong programming ...

AI and Data Engineer

Santa Clara, CA · On-site

$134K - $161K/yr

Extensive experience in natural language processing, text generation, and prompt engineering, with a deep understanding of the underlying principles and techniques. * Proficiency in programming ...

Text / Unstructured Data (NLP & GenAI) Building lowlatency realtime systems using deep learning, LLMs, prompt engineering, and agentic AI frameworks. This role requires strong expertise in Big Data ...

Hands-on experience using AI for document analysis, text summarization, and data extraction * Basic understanding of prompt engineering and structured prompting techniques * Strong written ...

Extensive experience in natural language processing, text generation, and prompt engineering, with a deep understanding of the underlying principles and techniques. * Proficiency in programming ...

AI Automation Analyst

Spring, TX · On-site

$130K - $150K/yr

Hands-on experience using AI for document analysis, text summarization, and data extraction * Basic understanding of prompt engineering and structured prompting techniques * Strong written ...

... prompt engineering advances to ensure cutting-edge solutions. Qualifications : Required : • ... raw text, specific industry encodings, graph data). • Familiarity or experience with Python ...

If you get excited about mixing prompt engineering with software engineering to unlock new AI ... text, layout, and visual generation * Develop complex prompts for new features using AI JSX ...

Design and implement prompt engineering strategies, agentic workflows, and orchestration frameworks ... By providing your phone number, you consent to: (1) receive automated text messages and calls from ...

Apply advanced prompt engineering techniques for accuracy and reusability. Lead design and ... Reply STOP to opt out of receiving telephone calls and text messages from Judge and HELP for help.

... text and language generation. · Data management, preprocessing, and feature engineering skills. · Expertise with prompt engineering techniques for guiding AI models. · Experience with cloud-based ...

Sr Data Scientist GenAI

Dallas, TX · On-site +1

$150K - $210K/yr

... embedding, search & retrieval, prompt engineering, RAG (Retrieval-Augmented Generation ... text) or emerging LLMs and agent-based systems. - Experience with open source LLMs & toolkits ...

... text and vision capabilities. You will work closely with cross-functional teams to build scalable ... Design and improve prompt engineering and context engineering workflows, including AI evaluation ...

... Prompt engineering optimization for large language models • Document AI pipelines: OCR/extraction, parsing, normalization, and text chunking for structured & unstructured data • Embedding ...

... PDFs, and text into structured data models * Experience building data pipelines that feed AI/ML ... Working knowledge of Claude (Anthropic) and GPT (OpenAI) model integration, prompt engineering, or ...

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Text Prompt Engineering information

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$32.5K

$63K

$95.5K

How much do text prompt engineering jobs pay per year?

As of Jun 8, 2026, the average yearly pay for text prompt engineering in the United States is $62,977.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,000.00 and $72,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Text Prompt Engineers when working with AI models, and how can they be addressed?

Text Prompt Engineers often encounter challenges such as ensuring prompts yield consistent and accurate responses from AI models and mitigating issues like model bias or ambiguous outputs. To address these, it’s important to iteratively test and refine prompts, collaborate closely with data scientists, and stay updated on model capabilities and limitations. Additionally, documenting prompt strategies and sharing learnings with the team can help streamline future projects and improve overall output quality.

What is text prompt engineering?

Text prompt engineering is the process of designing, refining, and optimizing prompts to guide AI language models, like ChatGPT, towards producing desired outputs. It involves understanding how AI interprets natural language and crafting instructions or queries that elicit specific, accurate, or creative responses. Prompt engineers experiment with phrasing, structure, and context to improve the model's performance on various tasks, such as content generation, summarization, or problem-solving. This emerging field is crucial for maximizing the effectiveness of AI in real-world applications.

What is the difference between Text Prompt Engineering vs Data Scientist?

AspectText Prompt EngineeringData Scientist
Required CredentialsKnowledge of NLP, AI, and prompt design; often self-taught or with specialized coursesDegree in Data Science, Computer Science, or related fields; certifications like CAP or DASCA
Work EnvironmentPrimarily remote, focused on AI platforms and language modelsVaries; offices, research labs, or remote, working with data analysis and modeling
Industry UsageUsed in AI development, chatbot design, and NLP applicationsApplied in finance, healthcare, tech, and research for data analysis and predictive modeling

While both roles involve working with data and AI, Text Prompt Engineering focuses on designing effective prompts for language models, whereas Data Scientists analyze data to extract insights and build models. The roles overlap in AI knowledge but differ in their primary tasks and industry applications.

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

To thrive as a Text Prompt Engineer, you need a strong grasp of natural language processing (NLP), prompt design best practices, and an understanding of AI model behavior, often supported by experience in linguistics or computer science. Familiarity with large language model platforms (such as OpenAI, Anthropic, or Google), version control tools, and prompt evaluation frameworks is common in this role. Exceptional critical thinking, creativity, and collaboration skills help engineers craft effective prompts and iterate quickly based on model outputs and team feedback. These competencies are crucial for maximizing AI performance, generating accurate results, and delivering real-world value from language models.

Can I become a AI prompt engineer with no experience?

Yes, it is possible to become a prompt engineer without prior experience, especially if you have a strong interest in AI, good problem-solving skills, and are willing to learn about language models and related tools. Building knowledge through online courses, tutorials, and practicing with AI platforms can help you develop the necessary skills for this role. Entry-level positions may require demonstrating your ability to craft effective prompts and understanding AI behavior.
More about Text Prompt Engineering jobs
Infographic showing various Text Prompt Engineering job openings in the United States as of May 2026, with employment types broken down into 93% Full Time, 5% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $62,977 per year, or $30.3 per hour.

Python Developer with LLM, GCP

Sparc Technology Services Inc

Irving, TX • On-site, Remote

$48 - $66.25/hr

Full-time

Posted 17 days ago


Job description

Python Developer data engineering GCP Working
Exp with LLMs etc
building custom Python applications for large-scale data
building pipelines for data processing and deploying in GCP
Solid foundation in Machine Learning
Extensive experience working with Large Language Models (LLMs) such as Gemini, Claude, and GPT with in-depth understanding of tokenization, embeddings, and context management.
Advanced expertise in Prompt Engineering, fine-tuning, and Retrieval-Augmented Generation (RAG) techniques.
Experience working with Vector databases and text embeddings.
Experience within Google Cloud environments (e.g., BigQuery, Cloud Run).

Flexible work from home options available.