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Text Prompt Engineering Jobs (NOW HIRING)

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

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

Own the AI orchestration layer -from prompt engineering to context management, tool calling, and ... Familiarity with speech-to-text, text-to-speech, or VAD technologies * Background in prompt ...

... and text data • Familiar with Large Language Models (LLMs), prompt engineering and their applications • Comfortable working in a fast paced, highly collaborative, dynamic work environment • ...

Build and productionize data pipelines (structured, text, documents, images) optimized for LLMs and ... Experience using MLflow for the full lifecycle: from experiment tracking and prompt engineering in ...

Senior Software Engineer, Agent

Palo Alto, CA · Remote

$144K - $190K/yr

... prompt engineering, context window management, multi-provider model routing (Claude, GPT, Gemini ... to-text, video generation) • Experience with agent frameworks (LangChain, AutoGPT, CrewAI, 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.

Full-time

Posted 18 days ago


Job description

OPPO AI Center is seeking a passionate AI Engineer to help build next-generation AI products and intelligent agent systems. In this role, you will design, develop, and deploy advanced LLM and AI Agent technologies that integrate text and vision capabilities. You will work closely with cross-functional teams to build scalable AI solutions and bring AI technologies into real-world products and user experiences.
Key Responsibilities:
• Develop and optimize AI applications based on LLMs and multimodal foundation models, with strong understanding of model quality, latency, and cost trade-offs.
• Design and improve prompt engineering and context engineering workflows, including AI evaluation, debugging, and tuning for real-world product scenarios.
• Build and improve AI agent systems with capabilities such as memory management, context management, and tool usage for production AI applications.
Requirements
Minimum Qualifications:
• Master's degree in CS, AI, ML, CV, NLP, or a related field; or Bachelor's degree with 2+ years of industry experience in related areas.
• Hands-on experience with LLM APIs and modern foundation models, with solid understanding of model trade-offs across quality, latency, scalability, and cost efficiency in real-world AI applications.
• Strong understanding of prompt engineering, context engineering, AI agent architectures, memory and context management, and tool-calling workflows, with the ability to independently perform AI system evaluation, debugging, tuning, and optimization.
Preferred Qualifications:
• Experience building and deploying AI agent systems, including tool-use agents, workflow automation agents, and multimodal AI applications in production environments.
• Familiarity with modern AI frameworks and ecosystems such as LangChain, OpenAI API, Anthropic API, Gemini API, vector databases, RAG pipelines, and agent orchestration frameworks.
• Strong problem-solving and communication skills, with the ability to rapidly prototype, iterate, and collaborate across research, engineering, and product teams in a fast-paced AI development environment.
Benefits
OPPO is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
The US base salary range for this full-time position is $100,000-$200,000 + bonus + long term incentives benefits. Our salary ranges are determined by role, level, and location.