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Ai Agent Manager Jobs in Virginia (NOW HIRING)

Tror AI for everyone

AI Agent Engineer

Mclean, VA · On-site

Job Title: - Senior AI Agent Engineer Location: - McLean, VA - 5 days onsite Employment Type ... Build orchestration logic to manage the lifecycle of subagents (initialization, delegation ...

Cliff Services Inc

AI Engineer/Architect

Vienna, VA · On-site

AI Agent Security * AI Risk Management * Enterprise AI Architecture * Azure AI Foundry * Microsoft Copilot Studio * Azure Kubernetes Service (AKS) * AI Compliance & Controls * Production Readiness

Headway Tek Inc

Agentic AI & Observability

Mclean, VA · On-site

$54 - $74/hr

Agentic AI & Observability location:MC lean, VA or Plano,TX(3-4 days hybrid) C2C or W2 Role Summary ... secrets-management, and data-protection requirements across agent and observability solutions.

Ll Oefentherapie

AI & Data Architect, US

Richmond, VA · On-site

$158 - $355/hr

AI Vector Search; Select AI / NL2SQL; Oracle AI Data Platform; GoldenGate; Object Storage ... management, and model lifecycle. - Agent runtimes, multi-agent orchestration, planning, memory ...

New

Lightedge

Sr. AI Integration Engineer

Ashburn, VA · On-site

$106K - $143K/yr

AI Agent & Workflow Lifecycle Management: Own the end-to-end lifecycle of AI agents and AI-driven workflows, from intake and requirements shaping through production readiness, deployment, monitoring ...

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Ai Agent Manager information

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$11

$26

$58

How much do ai agent manager jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for ai agent manager in Virginia is $26.29, according to ZipRecruiter salary data. Most workers in this role earn between $20.00 and $30.29 per hour, depending on experience, location, and employer.

What is an AI Agent Manager?

An AI Agent Manager is a professional responsible for overseeing the development, deployment, and maintenance of AI agents or systems. They coordinate teams, ensure AI performance aligns with objectives, and often require knowledge of AI tools, programming, and project management. This role involves managing AI workflows and optimizing agent interactions within an organization.

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

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

What cities in Virginia are hiring for Ai Agent Manager jobs?

Cities in Virginia with the most Ai Agent Manager job openings:

Ai Agent Manager jobs near you
Infographic showing various Ai Agent Manager job openings in Virginia as of August 2026, with employment types broken down into 80% Full Time, 19% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $54,677 per year, or $26.3 per hour.

AI Agent Engineer

Tror AI for everyone

Mclean, VA • On-site

Contractor

Re-posted 17 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