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Remote Prompt Engineering Jobs in Virginia (NOW HIRING)

GRVTY

Data Scientist - Cleared

Chantilly, VA · On-site +1

... remote work) and requires a TS/SCI + Poly clearance (acceptable to this customer). What You'll be Owning GRVTY is seeking a Data Engineer to join one of our top projects in Chantilly, VA. This role ...

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 ...

GRVTY

Data Scientist - Cleared

Chantilly, VA · On-site +1

$250K/yr

... remote work) and requires a TS/SCI + Poly clearance (acceptable to this customer). What You'll be ... The data engineer will work with and analyze our client's challenges and provide solutions by ...

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All JobsPrompt Engineering JobsRemote Prompt Engineering JobsRemote Prompt Engineering Jobs in Virginia

Remote Prompt Engineering information

See Virginia salary details

$17

$32

$47

How much do remote prompt engineering jobs pay per hour?

As of Jul 14, 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.

How to make $1000 a week remotely?

Remote prompt engineering can generate $1000 or more weekly by freelancing on platforms like Upwork or Fiverr, building a strong portfolio, and offering specialized skills in AI and NLP. Consistent work, high-demand projects, and efficient time management are key to reaching this income level.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and working in high-demand industries or companies. Compensation often includes base salary, bonuses, and stock options, particularly in tech giants or startups with significant growth potential.

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, and why are they important?

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.

Are prompt engineers still in demand?

Prompt engineering is a growing field as organizations seek professionals skilled in designing effective prompts for AI language models. Demand for prompt engineers is increasing across industries such as technology, healthcare, and finance, often requiring knowledge of AI tools and natural language processing. The role is expected to remain relevant as AI adoption expands.

What jobs make $3,000 a day?

High-paying jobs such as remote prompt engineering, specialized consulting, or executive roles can earn $3,000 or more per day, especially for professionals with advanced skills, experience, and in-demand expertise. These roles often require strong technical knowledge, certifications, and the ability to deliver high-value services on a freelance or contract basis.

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 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 July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $68,170 per year, or $32.8 per hour.
AI/ML Engineer - ACG / AEA

AI/ML Engineer - ACG / AEA

Connected Logistics

Springfield, VA • Remote

$155K - $165K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago

Job description

Description

Remote

Contingent Contract Award

6 month opportunity 

Springfield, VA


Connected Logistics is seeking an AI/ML Engineer to build and integrate machine learning components into enterprise workflows. The focus is on implementing models, RAG pipelines, and supporting services that enable automation, classification, retrieval, and intelligent decision support. Ideally, the engineer should have prior successes building and deploying RAG + ML services in production. This opportunity is expected to last for six (6) months with travel to Washington, DC.


Key Responsibilities:

  • Develop ML models and supporting services for classification, clustering, similarity search, and prediction.
  • Implement RAG pipelines: document ingestion, embedding generation, vector indexing, and retrieval tuning.
  • Build APIs and microservices to expose model capabilities to enterprise systems.
  • Integrate ML components into existing DevSecOps pipelines (Azure DevOps, CI/CD workflows).
  • Implement duplicate detection, ticket routing, SLA prediction, and root-cause assist features.
  • Optimize model performance for latency, throughput, and accuracy.
  • Conduct model evaluation, error analysis, and iterative tuning.
  • Work with Data Engineer to align data pipelines with model input requirements.
  • Ensure outputs are explainable, auditable, and compliant with governance controls.

Requirements

  • Minimum 10 years of experience in AI/ML engineering, software development, or data science.
  • Master's degree required in Computer Science, Engineering, or related field.
  • Must have an Active Public Trust clearance or higher.
  • Strong experience with Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).
  • Experience with embeddings, vector similarity search, and retrieval systems.
  • Experience building and deploying APIs or microservices for ML inference.
  • Hands-on experience with AWS and/or Azure environments.
  • Experience integrating into CI/CD pipelines and production systems.

Must-Have Skill Sets (Technical + Methodologies)

RAG Implementation (hands-on build experience)

  • Document ingestion + chunking strategies
  • Embedding generation and storage
  • Vector similarity search and retrieval optimization

  Machine Learning Model Development

  • Classification, clustering, and ranking models
  • Feature engineering and dataset preparation
  • Model tuning and evaluation

LLM Application Development

  • Prompt construction and chaining
  • Output validation and structured responses
  • Integration of LLMs into workflows (not just experimentation)

API and Service Development

  • RESTful API design and implementation
  • Serving ML models in production (FastAPI, Flask, etc.)
  • Stateless service design

CI/CD for ML Systems

  • Model deployment pipelines
  • Automated testing and validation before release
  • Version control for code + models

Cloud Deployment

  • Running ML workloads in AWS or Azure
  • Containerization (Docker)
  • Basic orchestration patterns (serverless or container-based)

Search and Similarity Systems

  • Embeddings + cosine similarity / ANN search
  • Duplicate detection patterns
  • Ranking and scoring logic

Performance Optimization

  • Latency reduction for inference
  • Efficient batching / caching strategies
  • Memory and compute-tuning

Total Rewards Statement:


We believe in fairness and clarity throughout our hiring process. The anticipated salary range for this position is $155,000.00 to $165,000.00 good faith range based on factors such as your experience, geographic location, and any applicable contractual requirements, and may vary slightly.


Beyond salary, we provide a robust benefits package and encourage ongoing professional development, because your growth and well-being matter to us. We're excited to support you in building a rewarding career with us!


Connected Logistics respects the need for confidentiality for all applicants.


Connected Logistics offers an excellent benefits package that includes health, dental, vision, life, and disability insurance, a great 401(k) package, and generous Paid Time Off.


EOE/Disability/Veterans

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