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Text Prompt Engineering Jobs (NOW HIRING)

Prompt Engineering, NL2SQL, Text-to-SQL systems Education / Experience / Certification Bachelor's degree in computer science or related field (required) 10+ years of experience as a Database ...

Design and implement AI solutions for multiple NLP tasks including text generation, summarization ... Familiarity with data preprocessing, prompt engineering, and performance tuning. Excellent problem ...

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 ...

Copilot Engineer

Charlotte, NC · On-site

$60 - $65/hr

... use Copilot & Prompt Engineering * Hands on experience using copilot for instructions, prompts ... Frequency varies for text messages. Message and data rates may apply. Carriers are not liable for ...

Experience working with speech and text data * Familiar with Large Language Models (LLMs), prompt engineering and their applications * Comfortable working in a fast paced, highly collaborative ...

CCaaS Google Data Engineer

Sunrise, FL · On-site

$109K - $131K/yr

... text-to-speech. * Architect secure, resilient cloud infrastructure on major cloud services ... Experience with Xgboost, SARIMA, Prophet, prompt engineering, and TensorFlow. * Understanding of ...

Showing results 41-60

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 Aug 11, 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.
More about Text Prompt Engineering jobs
Infographic showing various Text Prompt Engineering job openings in the United States as of August 2026, with employment types broken down into 91% Full Time, 4% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $62,977 per year, or $30.3 per hour.

Senior Software Engineer - Contact Center Technology

ASCENSUS

Chicago, IL • Remote

$126K - $166K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 24 days ago


Ascensus rating

8.2

Company rating: 8.2 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

45th of 150 rated financial services


Job description

Ascensus is the leading independent technology and service platform powering savings plans across America, providing products and expertise that help nearly 16 million people save for a better today and tomorrow.

Section 1: Position Summary

At Ascensus, we are building a team that is empowered to use AI to solve the business needs by having a rapid development and deployment pipeline with a focus on rapid iteration, continuous delivery, and intelligent automation.

We are looking to add a software engineer who will design, develop, and support conversational AI solutions that enhance customer and associate experiences across our contact center platforms. This role combines software engineering, generative AI, prompt engineering, and customer engagement technologies to deliver virtual agents, intelligent self-service capabilities, agent assist solutions, and AI-powered business workflows. If you're AI-Forward and excited to explore and apply the latest tools and technologies to solve real-world business problems, this is the role for you. You'll work with a modern tech stack including Python, .NET, Azure OpenAI, LangChain, PostgreSQL, Docker, Cursor, Git, Azure DevOps, NICE CXone, AI Agents, and conversational AI technologies to deliver high value software to our business.

Section 2: Job Functions, Essential Duties and Responsibilities

Design, develop, test, and maintain conversational AI experiences including voice bots, chatbots, virtual assistants, and agent-assist solutions using NICE CXone, Azure OpenAI, and related technologies.

Create and optimize conversational flows, prompts, intents, and knowledge retrieval mechanisms to improve customer and associate experiences.

Analyze conversation transcripts and interaction data to continuously improve AI accuracy, containment rates, and customer satisfaction.

Develop integrations between NICE CXone and internal systems using APIs, event-driven architectures, and AI services.

Support the design and implementation of intelligent routing, self-service, and automation capabilities within the contact center ecosystem.

Partner with contact center business teams to identify opportunities for AI-driven process automation and customer experience improvements.

Collaborate with cross-functional teams to integrate AI capabilities using Azure OpenAI, Langchain, and AI Agents.

Apply prompt engineering techniques to optimize LLM interactions for precision, consistency, and business value.

Monitor AI solution performance and implement safeguards to ensure accuracy, compliance, reliability, and responsible AI usage.

Build and maintain containerized applications using Docker and deploy via Azure DevOps pipelines.

Work with PostgreSQL and other data technologies to design efficient, reliable data models.

Develop and consume REST APIs to enable seamless integration across services and platforms.

Participate in sprint planning, estimation, and retrospectives as part of an Agile Scrum team.

Contribute to the evolution of our AI-driven development environment using tools like Cursor.

Stay current with emerging technologies and bring a mindset of continuous learning and experimentation.

Section 3: Experience, Skills, Knowledge Requirements

A strong interest in leveraging AI and the latest tools to drive innovation and efficiency.

Extensive experience using .NET to develop web applications and back-end services

Extensive experience designing, developing, and integrating REST APIs in distributed systems and enterprise applications.

Ability to design, develop, test, and maintain scalable MCP server architectures using Python

Experience with Docker, Git, Azure DevOps, CI/CD pipelines, automated testing, and infrastructure as code.

Experience building AI solutions using Azure OpenAI, LangChain, Retrieval-Augmented Generation (RAG), AI agents, prompt engineering techniques, and related AI development frameworks.

Experience with prompt engineering and optimizing LLM interactions for accuracy and reliability.

Experience with NICE CXone or similar contact center platforms such as Genesys, Five9, Amazon Connect, or Cisco Contact Center.

Understanding of contact center operations, including inbound and outbound customer engagement.

Familiarity with IVR design, intelligent routing, call flows, skills-based routing, and self-service automation.

Experience integrating contact center platforms with CRM, case management, and enterprise business systems.

Experience designing, implementing, or supporting virtual agents, chatbots, voice bots, or conversational AI platforms.

Understanding of natural language processing (NLP), natural language understanding (NLU), speech recognition, and text-to-speech technologies.

Experience evaluating and improving AI-generated responses for accuracy, effectiveness, and customer experience outcomes.

Experience working with other developers, quality engineers (QE), ops engineers and support engineers to ensure smooth deployment and continual operation

Strong problem-solving skills, attention to detail, and a passion for learning and applying new technologies.

Excellent communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders.

Familiarity or experience with Agile engineering practices (test driven development, continuous integration and pair programming, etc.

Ability to work with legacy systems while contributing to modernization efforts.

Familiarity with Agile methodologies and open-source development practices.

The national average salary range for this role is$100K-160K in base pay, exclusive of any bonuses and benefits.This base salary range represents the low and high end of the salary range for this position. Actual salary offered will vary and may be above or below the range based on various factors including but not limited to location, experience, performance, and internal pay alignment. We do not anticipate that candidates hired will begin at the top of the range however, from time to time, it may occur on a case-by-case basis. Other rewards and benefits may include: 401(k) match, Medical, Dental, Vision, Paid-Time-Off, etc. For more information, please visitcareers.ascensus.com/#Benefits

Be aware of employment fraud. All email communications from Ascensus or its hiring managers originate from @ascensus.com or @futureplan.com email addresses. We will never ask you for payment or require you to purchase any equipment. If you are suspicious or unsure about validity of a job posting, we strongly encourage you to apply directly through our website.


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