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Remote Prompt Engineering Jobs in Virginia (NOW HIRING)

AvePoint

Technical Account Manager- Google

Richmond, VA · On-site +1

$75K - $100K/yr

Becoming a trusted customer advocate by ensuring we are prompt and professional with all ... Performing remote or onsite platform integration engagements for existing clients * Delivering ...

Unacast

Senior Data Analyst/Scientist

Ashburn, VA · Remote

$110K - $130K/yr

... engineering environment. * Familiarity with AI-specific risks including prompt injection, data ... Other Info This is a remote position that may require occasional travel. Candidates must reside in ...

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Remote Prompt Engineering information

See Virginia salary details

$17

$32

$47

How much do remote prompt engineering jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for remote prompt engineering in Virginia is $32.77, according to ZipRecruiter salary data. Most workers in this role earn between $26.20 and $37.88 per hour, depending on experience, location, and employer.

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.

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 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 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 the most commonly searched types of Prompt Engineering jobs in Virginia?

The most popular types of Prompt Engineering jobs in Virginia are:

What are popular job titles related to Remote Prompt Engineering jobs in Virginia?

For Remote Prompt Engineering jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Prompt Engineering jobs in Virginia look for?

The top searched job categories for Remote Prompt Engineering jobs in Virginia are:

What cities in Virginia are hiring for Remote Prompt Engineering jobs?

Cities in Virginia with the most Remote Prompt Engineering job openings:

Remote Prompt Engineering jobs near you
Infographic showing various Remote Prompt Engineering job openings in Virginia as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $68,170 per year, or $32.8 per hour.

SENIOR AMAZON BEDROCK/RAG ENGINEER

Axyde Analytics

Midlothian, VA • Remote

$99K - $135K/yr

Full-time

Posted 4 days ago

Job description

Axyde Analytics seeks a senior Amazon Bedrock engineer to configure secure retrieval-augmented generation, document processing, structured extraction, source attribution, and policy-mapping capabilities for a federal analytics platform.

Responsibilities

  • Configure Amazon Bedrock managed Knowledge Bases and approved managed retrieval components.

  • Implement secure ingestion and indexing of approved websites, linked documents, PDFs, and enterprise data.

  • Configure foundation models, embedding models, chunking, retrieval, prompts, schemas, and guardrails.

  • Extract structured issues, requirements, entities, relationships, and exact supporting source excerpts.

  • Implement citation-backed responses and traceable mappings between source documents and Government directives.

  • Ensure prompts and Government data remain within the authorized environment and are not used to train external models.

  • Develop measurable evaluation criteria for extraction accuracy, retrieval quality, citation correctness, and hallucination control.

  • Support OCR and managed natural-language-processing services when approved.

  • Document exact models, versions, configurations, limitations, and dependencies.

  • Support live demonstrations, production hardening, monitoring, and continuous improvement.

Required Experience

  • Direct production experience with Amazon Bedrock and Bedrock Knowledge Bases.

  • Experience with managed web crawling, linked-document ingestion, parsing, embeddings, vector retrieval, structured extraction, and RAG evaluation.

  • Strong understanding of prompt security, model governance, guardrails, source attribution, and sensitive-data handling.

  • Experience implementing AI solutions in federal, healthcare, financial, or similarly regulated environments.

  • Ability to work exclusively within an approved AWS managed-service architecture.

Current Baseline

The current baseline includes Amazon Bedrock, managed Knowledge Bases, approved Bedrock-managed retrieval, Claude Sonnet, Titan Text Embeddings, Guardrails, S3, Step Functions, and AWS-native security and monitoring. Exact services, models, versions, and regions will be governed by Axyde’s final approved technical baseline.

Engagement

U.S. citizenship required. Remote within the United States. Immediate availability for proposal validation and demonstration development is preferred. Continued work is contingent upon award.