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Home Based Prompt Engineering Jobs in Virginia (NOW HIRING)

... LLM-based applications (prompt engineering, RAG architectures, agent frameworks) * Direct experience with Amazon Bedrock, including Agent configuration, Knowledge Base setup, Guardrails, and ...

Agentic Software Engineer III

Rosslyn, VA

$65.50 - $88/hr

Experience with generative artificial intelligence, prompt engineering, software development life cycle processes, and systems-based problem solving * Ability to travel 10-50%, on average, based on ...

All from the comfort of your home. Why Join Our Platform? * Earn incrementally higher pay for each ... Deep knowledge of ChatGPT capabilities including prompt engineering, conversational AI interaction ...

Showing results 21-40

Home Based Prompt Engineering information

What is the difference between Home Based Prompt Engineering vs Remote AI Content Specialist?

AspectHome Based Prompt EngineeringRemote AI Content Specialist
Required CredentialsBasic understanding of AI prompts, no formal certification neededExperience in content creation, possibly some AI tool familiarity
Work EnvironmentHome-based, flexible hoursHome-based, project or task-based
Industry UsageAI development, chatbot training, prompt optimizationContent marketing, social media, digital content creation
Common Search IntentJobs involving AI prompt design from homeRemote content creation roles involving AI tools

Home Based Prompt Engineering focuses on designing and refining prompts for AI models, often requiring technical understanding of AI systems. In contrast, Remote AI Content Specialists create digital content using AI tools, emphasizing content skills. Both roles are home-based and industry-related but differ in technical depth and primary tasks.

Are home based prompt engineers still in demand?

Home-based prompt engineering is increasingly in demand as AI language models are integrated into various applications. Professionals with skills in prompt design, natural language processing, and familiarity with AI tools are sought after across industries, especially in remote work environments. The role often requires strong communication skills and knowledge of AI platforms like GPT or similar models.

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 cities in Virginia are hiring for Home Based Prompt Engineering jobs?

Cities in Virginia with the most Home Based Prompt Engineering job openings:

A.I. Process Integration Engineer - SME - TS & CI Poly required to apply - NCR

Reston, VA β€’ On-site

$117K/yr

Other

Re-posted 5 days ago


Job description

AI Process Integration Engineer

Job Type: Full‑Time

Job Summary

The AI Process Integration Engineer sits at the intersection of artificial intelligence deployment and mission workflow optimization - responsible for bridging the gap between approved, available AI/ML tools and their effective operational use across intelligence analysis, targeting, and screening and vetting workflows. This role does not wait for new tools to be approved; it maximizes the mission value of what is already on the network by redesigning the processes around those tools, configuring them for mission‑specific use cases, and ensuring analysts can leverage them from Day 1.

Key Responsibilities
  1. AI Tool Evaluation & Configuration

    • Assess approved AI/ML tools currently available on the customer network and evaluate their operational readiness, configuration gaps, and underutilization.
    • Configure, optimize, and integrate approved tools into existing analytic and targeting workflows without introducing unapproved capabilities or triggering additional review board requirements.
    • Develop mission‑specific use‑case configurations that align tool functionality to analyst tasks - entity triage, credibility scoring, pattern correlation, document production, and RFI processing.
    • Maintain tool performance baselines and identify configuration adjustments that improve output accuracy, speed, and analyst adoption.
  2. Workflow Analysis & Process Redesign

    • Map current‑state analytic and operational workflows to identify where approved AI tools can eliminate manual bottlenecks, reduce redundant data entry, and compress cycle times.
    • Design optimized future‑state workflows that embed AI tool touchpoints at the highest‑friction points in the intelligence production and targeting cycle.
    • Develop before/after process documentation with measurable performance targets tied directly to mission outcomes.
    • Maintain SOPs and workflow guides that reflect the integrated AI‑enabled process architecture.
  3. Prompt Engineering & Tool Enablement

    • Build mission‑specific prompt libraries, Boolean‑to‑AI logic translation guides, and structured templates that make approved tools immediately usable by analysts without requiring technical expertise.
    • Develop a Document Support Playbook Suite covering draft assist, tradecraft review, source synthesis, consistency checking, and classification review workflows.
    • Ensure all prompt engineering products are tool‑agnostic and adaptable to any customer‑approved platform upgrade or replacement.
  4. Performance Measurement & Continuous Improvement

    • Establish KPIs tracking AI tool utilization rates, analyst productivity gains, cycle time reductions, and product quality improvements.
    • Provide leadership with data‑driven evidence supporting review board decisions to expand AI tool access or activate additional use cases.
    • Apply Lean Six Sigma and continuous improvement methodologies to iteratively refine AI‑integrated workflows based on operational feedback.
  5. Stakeholder Collaboration & Change Management

    • Work directly with analysts, targeters, mission leads, and IT teams to drive adoption of AI‑integrated workflows through hands‑on demonstration, embedded support, and structured enablement.
    • Develop transition plans and training materials that ensure smooth integration of AI tools into daily mission operations with zero workflow disruption.
    • Serve as the operational bridge between the technical AI/ML engineering team, the analytic workforce, and program leadership.
Required Qualifications
  • Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
  • Experience: 10+ years of experience in AI/ML tool deployment, systems integration, or business process engineering; at least 5 years supporting IC, DoD, or Federal law enforcement analytic environments.
  • Technical Skills: Proficiency in AI/ML tool configuration, prompt engineering, workflow modeling (BPMN), and data pipeline management; experience with IC‑approved analytic platforms and multi‑classification network environments.
  • Methodologies: Working knowledge of Lean Six Sigma, Agile, and continuous improvement frameworks applied to operational or intelligence environments.
  • Soft Skills: Strong analytical thinking, clear written and verbal communication, and the ability to translate technical AI capability into practical mission value for non‑technical analysts.
  • Clearance: Active TS/SCI with CI Polygraph required.
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