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Ai Tasker Jobs in Virginia (NOW HIRING)

Tror AI for everyone

AI Agent Engineer

Mclean, VA · On-site

You will enable AI to handle specialized tasks--architecture planning, frontend/backend development, debugging, and security reviews--while maintaining context isolation. Responsibilities * Subagent ...

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Ai Tasker information

What is an AI Tasker?

An AI Tasker is responsible for training, testing, and refining artificial intelligence models by completing various tasks such as labeling data, reviewing AI-generated content, and providing feedback on model outputs. This role helps improve AI systems by ensuring accuracy and relevance in their responses. AI Taskers often work remotely and require attention to detail, critical thinking skills, and familiarity with AI tools.

What does an AI Tasker do?

As an AI Tasker, your day often involves reviewing and managing a variety of AI-assisted assignments such as data categorization, process automation, or QA testing on digital platforms. You may coordinate with team members to clarify project requirements, set priorities, and troubleshoot technical issues that arise during task execution. Regular collaboration with both AI engineers and project managers helps ensure deliverables meet quality standards and deadlines. The workload can be dynamic, requiring flexibility and proactive communication to handle shifting project demands efficiently.

What are the key skills and qualifications needed to thrive as an AI Tasker?

To thrive as an AI Tasker, you need a strong understanding of artificial intelligence concepts, data analysis, and problem-solving abilities, often supported by a background in computer science or a related field. Familiarity with AI platforms, automation tools, and workflow management systems is typically required, along with knowledge of APIs and task management software. Strong communication, attention to detail, and adaptability help AI Taskers excel when collaborating and managing diverse, technology-driven assignments. These capabilities are critical for ensuring accurate execution of AI-powered tasks and effective integration with business processes.

What is the easiest AI Tasker job to get?

The easiest AI Tasker jobs typically involve simple data labeling, annotation, or basic content moderation tasks that require minimal technical skills. These roles often have low entry barriers, do not require advanced certifications, and can be performed remotely with basic computer literacy and attention to detail.

What are the most commonly searched types of Ai Tasker jobs in Virginia?

The most popular types of Ai Tasker jobs in Virginia are:

What are popular job titles related to Ai Tasker jobs in Virginia?

For Ai Tasker jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Ai Tasker jobs in Virginia look for?

The top searched job categories for Ai Tasker jobs in Virginia are:

What cities in Virginia are hiring for Ai Tasker jobs?

Cities in Virginia with the most Ai Tasker job openings:

Ai Tasker jobs near you
Infographic showing various Ai Tasker job openings in Virginia as of August 2026, with employment types broken down into 71% Full Time, 27% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

AI Agent Engineer

Tror AI for everyone

Mclean, VA • On-site

Contractor

Re-posted 2 days ago

Job description

Job Title: - Senior AI Agent Engineer

Location: - McLean, VA - 5 days onsite

Employment Type: - Contract

Need 10+ years of experience resumes and need locals to VA or nearby location.

Job Description: -

We are seeking a forward-thinking AI SDLC Engineer to transform our development processes from linear automation to an agentic, multi-agent workflow. The ideal candidate will design, build, and deploy specialized AI subagents (e.g., using frameworks like LangChain, CrewAI, or Claude Code) that collaborate to create production-grade software. You will enable AI to handle specialized tasks—architecture planning, frontend/backend development, debugging, and security reviews—while maintaining context isolation. Responsibilities

• Subagent Architecture & Creation: Design and implement task-specific AI subagents (e.g., ""Code Reviewer,"" ""SQL Expert,"" ""Frontend Builder"") with dedicated system prompts, tool access, and context boundaries.

• Orchestration & Workflow Automation: Build orchestration logic to manage the lifecycle of subagents (initialization, delegation, execution, and cleanup) using agentic frameworks.

• AI-Driven SDLC Integration: Implement agentic workflows across the entire SDLC, from requirements gathering and architecture design to automated testing, code review, and deployment.

• Context & Memory Management: Optimize AI performance by isolating noisy, long-running tasks into subagents, ensuring the main agent remains efficient and context-aware.

• Tooling & Integration: Integrate AI agents with internal development tools, including Bitbucket, Jira, ServiceNow and CI/CD pipelines.

• Performance Evaluation: Monitor, evaluate, and refine agentic workflows to improve code quality, reduce toil, and accelerate release cycles