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Associate Ai Agent Developer 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: - Contract Need 10+ years of experience resumes and need locals to VA or nearby location. - We are ...

Trilagen

Senior Sales Executive - Agentic AI

Reston, VA · On-site

Cross-sell across all three Trilagen practices - AI Agent Engineering, Cloud (AWS & Oracle OCI), and Identity Security (Okta & SailPoint ISC). Every engagement is a door into the other two. Territory ...

Purple Drive

Gen AI Engineer [Python, LLM]

Mclean, VA · On-site

Gen AI Engineer (LLM, LangChain, AI Agents) Experience: 8-10 Years Job Summary We are seeking a Gen AI Engineer with strong expertise in Python, Large Language Models (LLMs), and AI agent development ...

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All JobsAssociate Ai Agent Developer JobsAssociate Ai Agent Developer Jobs in Virginia

Associate Ai Agent Developer information

What is the difference between Associate Ai Agent Developer vs Machine Learning Engineer?

AspectAssociate Ai Agent DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or Master's in CS, Data Science, or related; advanced certifications
Work EnvironmentTech companies, AI startups, R&D labsTech firms, AI companies, research institutions
Employer & Industry UsageDevelops AI agents, chatbots, virtual assistantsDesigns ML models, algorithms, data pipelines
Common Search & ComparisonOften compared for entry-level AI rolesMore advanced, research-focused roles

The Associate Ai Agent Developer typically focuses on building and maintaining AI agents like chatbots and virtual assistants, often at an entry to mid-level. In contrast, a Machine Learning Engineer develops complex ML models and algorithms, usually requiring more advanced skills and experience. Both roles are vital in AI development but differ in scope, complexity, and specialization.

What are the most commonly searched types of Ai Agent Developer jobs in Virginia? The most popular types of Ai Agent Developer jobs in Virginia are:
What are popular job titles related to Associate Ai Agent Developer jobs in Virginia? For Associate Ai Agent Developer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Associate Ai Agent Developer jobs in Virginia look for? The top searched job categories for Associate Ai Agent Developer jobs in Virginia are:
What cities in Virginia are hiring for Associate Ai Agent Developer jobs? Cities in Virginia with the most Associate Ai Agent Developer job openings:
Associate Ai Agent Developer jobs near you
Infographic showing various Associate Ai Agent Developer job openings in Virginia as of June 2026, with employment types broken down into 46% Full Time, 38% Part Time, and 16% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

AI Agent Engineer

Tror AI for everyone

Mclean, VA • On-site

Contractor

Posted 11 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