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Manager Ai Agent Engineer Jobs in Washington (NOW HIRING)

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 ...

Senior AI Agent Engineer - Agentic

Reston, VA · On-site

$108K - $149K/yr

AI Engineer with expertise building agentic software development platforms using AWS, Strands Agents, Bedrock, Neptune, RDS, Step Functions, and Python. Experienced in code understanding ...

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Manager Ai Agent Engineer information

What is the difference between Manager Ai Agent Engineer vs Data Scientist?

AspectManager Ai Agent EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI/ML toolsBachelor's or Master's in CS, Statistics, or related fields; proficiency in data analysis and modeling
Work EnvironmentDeveloping, deploying, and managing AI agents; cross-functional teamsAnalyzing data, building models, and deriving insights; research-focused
Employer & Industry UsageTech companies, AI startups, enterprises implementing AI solutionsTech firms, finance, healthcare, research institutions

The Manager Ai Agent Engineer focuses on leading AI agent development and deployment, managing teams, and ensuring AI solutions meet business needs. In contrast, Data Scientists primarily analyze data, build predictive models, and generate insights. Both roles require strong technical skills, but their core responsibilities and work environments differ significantly.

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Cities in Washington with the most Manager Ai Agent Engineer job openings:

AI Agent Engineer

Tror AI for everyone

Mclean, VA • On-site

Contractor

Re-posted yesterday


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