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Remote Prompt Engineering Jobs in Dallas, TX (NOW HIRING)

Performacentric

Full Stack Developer

Dallas, TX · On-site +1

Remote (Preferred: Philippines, Latin America, or North America) Employment Type: Full-Time / ... Support prompt engineering and AI workflow automation. * Develop integrations between AI services ...

UnitedHealth Group

Lead AI Engineer- Remote

Richardson, TX · On-site +1

$93K - $122K/yr

Leverage and adapt LLMs; perform prompt engineering, grounding, guard railing, and domain adaptation for healthcare terminology and tasks * Design intelligent frameworks and finetune models for ...

UnitedHealth Group

Lead AI Engineer- Remote

Richardson, TX · On-site +1

$93K - $122K/yr

Leverage and adapt LLMs; perform prompt engineering, grounding, guard railing, and domain adaptation for healthcare terminology and tasks * Design intelligent frameworks and finetune models for ...

Confie

AI Engineer

Addison, TX · On-site +1

$110K - $140K/yr

Flexible work options, including remote and hybrid opportunities, if eligible * Retirement Plan ... Expertise in prompt engineering including chain-of-thought, few-shot learning, and structured ...

McKesson

AI Product Engineer

Irving, TX · Remote

This position is remote and candidates must reside within commuting distance of either The ... Familiarity with AI governance, model evaluation, prompt engineering, and solution monitoring.

McKesson

AI Product Engineer

Irving, TX · Remote

This position is remote and candidates must reside within commuting distance of either The ... Familiarity with AI governance, model evaluation, prompt engineering, and solution monitoring.

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All JobsPrompt Engineering JobsRemote Prompt Engineering JobsRemote Prompt Engineering Jobs in Dallas, TX

Remote Prompt Engineering information

See Dallas, TX salary details

$17

$32

$47

How much do remote prompt engineering jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for remote prompt engineering in Dallas, TX is $32.70, according to ZipRecruiter salary data. Most workers in this role earn between $26.15 and $37.79 per hour, depending on experience, location, and employer.

What is the difference between Remote Prompt Engineering vs Remote Data Annotation Specialist?

AspectRemote Prompt EngineeringRemote Data Annotation Specialist
Required CredentialsBasic understanding of AI, NLP, and scripting skillsAttention to detail, familiarity with annotation tools, no formal certifications required
Work EnvironmentCollaborative with AI/ML teams, remote setupIndependent annotation tasks, remote or on-site
Industry UsageAI development, NLP projects, machine learningData labeling for AI training datasets
Search & Comparison IntentUnderstanding roles in AI development, job requirementsData labeling jobs, annotation tasks, related roles

Remote Prompt Engineering involves designing and refining prompts for AI models, requiring some technical skills and collaboration with AI teams. In contrast, Remote Data Annotation Specialists focus on labeling data to train AI systems, emphasizing attention to detail. Both roles are essential in AI development but differ in skills and daily tasks.

What are some common challenges faced by remote prompt engineers, and how can they be addressed?

Remote prompt engineers often face challenges related to communication and collaboration, especially when working across time zones and with interdisciplinary teams. Staying updated on rapidly evolving AI technologies and understanding nuanced user requirements can also be demanding. To address these, prompt engineers can leverage collaborative tools, maintain clear documentation, and participate in regular team syncs. Building a habit of continuous learning and engaging in knowledge-sharing sessions helps keep skills relevant and fosters a sense of connection despite remote work.

What are the key skills and qualifications needed to thrive as a remote prompt engineer?

To thrive as a Remote Prompt Engineer, you need a strong background in natural language processing, programming (often Python), and an understanding of AI/ML concepts, typically supported by a relevant degree or industry experience. Familiarity with large language models (like OpenAI's GPT), prompt optimization tools, and version control systems such as Git is common. Creativity, problem-solving, and strong written communication are vital soft skills for designing effective prompts and collaborating remotely. These skills ensure the development of high-performing AI solutions and seamless teamwork in distributed environments.

What is remote prompt engineering?

Remote prompt engineering is the practice of designing and refining prompts for AI language models, such as ChatGPT, while working from a remote location. Prompt engineers craft instructions or questions to optimize the model’s responses for specific tasks or applications. This role typically involves understanding both the capabilities and limitations of AI systems, as well as the needs of end users or clients. Remote prompt engineers collaborate online with teams and may work for tech companies, research organizations, or as independent contractors.

Are remote prompt engineers still in demand?

Remote prompt engineers are currently in demand as organizations seek expertise in designing effective prompts for AI models. The role often requires skills in natural language processing, AI tools, and continuous learning to keep up with evolving technologies. Demand is driven by the growth of AI applications across various industries.
What are the most commonly searched types of Prompt Engineering jobs in Dallas, TX? The most popular types of Prompt Engineering jobs in Dallas, TX are:
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What job categories do people searching Remote Prompt Engineering jobs in Dallas, TX look for? The top searched job categories for Remote Prompt Engineering jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Remote Prompt Engineering jobs? Cities near Dallas, TX with the most Remote Prompt Engineering job openings:
Remote Prompt Engineering jobs near you
Infographic showing various Remote Prompt Engineering job openings in Dallas, TX as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $68,020 per year, or $32.7 per hour.

Lead AI Engineer, Business Operations (Hybrid or Remote)

Afl Telecommunications Llc

Dallas, TX • On-site, Remote

$98K - $129K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 5 days ago

Job description

AFL manufactures industry-leading fiber optic cable, connectivity and accessories and provides engineering and installation services for some of the largest telecom customers in the world. Our company was founded in 1984 with a single fiber optic cable and today, we manufacture thousands of products, generate an excess of $2B in revenue, and employ approximately 11,000 associates worldwide. At AFL, we recognize that our employees are our greatest asset. We hire and train each individual, investing in them to ensure success in their careers. With a commitment to professional development and growth, let us connect you to your next career opportunity. 

What We Offer:  

  • Flexible time off policy 
  • 401K Company match (up to 4% — dollar for dollar) 
  • Professional development, training, and tuition reimbursement programs 
  • Excellent medical, dental, vision, and life insurance policy options 
  • Opportunities for career advancement with an industry leading company! 

We are seeking a Lead AI Engineer to join our Business Operations team. This position may be able to work remotely from anywhere within the United States.  

The Lead AI Engineer is the first engineering hire on AFL's AI Enablement team, responsible for designing, building, and deploying agentic AI systems that automate the operational backbone of the business through workflow orchestration, model adaptation, and analytics. Working directly with the AI Enablement Manager, the Lead AI Engineer will help lay the technical foundation the rest of the team will build on — including model selection and management, deployment posture, orchestration patterns, evaluation and audit. As the team grows, an AI Product Manager and AI Operations Specialists will join to take on intake, sequencing, stakeholder coordination, and product ownership of deployed solutions, allowing engineers to stay focused on build work. 

Responsibilities:  

Key responsibilities/essential functions include: 

Architecture & Technical Foundation  

  • Establishes the architectural patterns, evaluation practices, and deployment standards for the team 
  • Makes framework and model recommendations that set the foundation for how the team builds — evaluates orchestration frameworks, selects deployment patterns, trains and fine-tunes models, and determines where managed platforms end and custom build begins 

Solution Design & Delivery  

  • Translates proposed business solutions into technical plans — defines product life cycles, prioritizes the backlog, and breaks initiatives into buildable work 
  • Owns solutions end-to-end: technical planning, architecture, build, deploy, and the monitoring that keeps them honest in production 

Production Reliability  

  • Builds the monitoring, evaluation, and regression detection systems that keep production agents reliable — including logging, performance benchmarking, and feedback loops that surface drift early 

Governance & Collaboration  

  • Partners with data governance to ensure solutions meet compliance, data quality, and operational standards 

Personal Qualities:  

  • Innovative and tech-savvy, with deep curiosity about emerging AI capabilities and how to apply them 
  • Analytical and detail-oriented, with a strong engineering mindset 
  • Collaborative and communicative, able to translate complex technical concepts for non-technical stakeholders 
  • Self-directed and accountable, able to set technical direction and drive execution independently 

Qualifications:  

  • Bachelor's degree in Computer Science or related field, or equivalent experience 
  • 7+ years of software engineering experience with a strong full-stack foundation — backend services, API design, system integration, and data infrastructure 
  • Recent hands-on experience building AI or LLM-backed systems and shipping them to production 
  • Experience architecting solutions from scratch and owning them through deployment, observability, testing, and ongoing reliability 
  • Experience with AI development practices — model selection, fine-tuning, prompt engineering, evaluation frameworks, and understanding when each approach is the right fit 
  • Proficiency in Python; experience with cloud platforms 
  • Experience mentoring engineers and setting technical direction across multiple initiatives 
  • Strong communication skills with both technical and non-technical stakeholders

Working Conditions:  

  • Environment: Remote work environment (US-based). 
  • Travel: Occasional travel (domestic) as needed. 

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