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Associate Ai Agent Developer Jobs in Washington (NOW HIRING)

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 ...

Associate AI Engineer Innovative Defense Technologies (IDT), provider of cutting-edge cloud-based ... Stay current on advances in LLMs, agent frameworks, orchestration methods, and applied AI ...

Practical experience with agent frameworks (AutoGen, CrewAI, Agno) and MCP/tool-use patterns ... Azure Data Scientist Associate (DP-100) Skills: Azure DevOps,GitHub services.

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 ...

The AI Agent & ML Engineer will design, build, and optimize intelligent agents powered by advanced machine learning models, enabling process automation and decision support across Bausch + Lombs ...

ServiceNow AI Developer

Chantilly, VA · Remote

$55.25 - $76/hr

... multi-agent orchestration frameworks. • Configure and optimize Now Assist, Predictive ... prompt engineering, and AI workflow orchestration • Experience integrating ServiceNow with ...

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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 Washington? The most popular types of Ai Agent Developer jobs in Washington are:
What job categories do people searching Associate Ai Agent Developer jobs in Washington look for? The top searched job categories for Associate Ai Agent Developer jobs in Washington are:
What cities in Washington are hiring for Associate Ai Agent Developer jobs? Cities in Washington with the most Associate Ai Agent Developer job openings:

AI Agent Engineer

Tror AI for everyone

Mclean, VA • On-site

Contractor

Posted 23 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