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Ai Agent Developer Jobs in Laurel, MD (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 ...

Infosat IT Services LLC

Agentic AI & Observability

Mclean, VA · On-site

$54 - $74/hr

... in AI agent development, MCP (Model Context Protocol) server development, observability, data analytics, and cloud-native engineering . The candidate will design and build intelligent agents, MCP ...

Klaxontech

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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Ai Agent Developer information

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$28.8K

$47.5K

$98.7K

How much do ai agent developer jobs pay per year?

As of Aug 31, 2026, the average yearly pay for ai agent developer in Laurel, MD is $47,521.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,700.00 and $50,600.00 per year, depending on experience, location, and employer.

What is an AI agent developer?

An AI Agent Developer designs, builds, and optimizes intelligent software agents that can autonomously perform tasks, make decisions, and interact with users or other systems. This role involves working with machine learning, natural language processing, reinforcement learning, and multi-agent systems to create adaptive and efficient AI solutions. Developers in this field often utilize frameworks like LangChain, AutoGPT, or OpenAI API to enhance agent capabilities. Their work spans various industries, including customer service automation, finance, gaming, and robotics.

What are some common challenges faced by AI agent developers in their daily work?

AI Agent Developers often encounter challenges such as managing large and complex datasets, optimizing agent performance, and ensuring models behave ethically and reliably in unpredictable environments. It’s common to iterate frequently on prototypes, test against edge cases, and fine-tune algorithms based on real-world feedback. Collaboration with data scientists, software engineers, and stakeholders is crucial to understand project goals and adapt solutions accordingly. Overcoming these challenges requires technical flexibility, persistence, and a strong teamwork mindset.

What are the key skills and qualifications needed to thrive in the AI agent developer position, and why are they important?

To thrive as an AI Agent Developer, you need strong programming skills (particularly in Python), a deep understanding of machine learning concepts, and a relevant degree in computer science or a related field. Expertise with AI development frameworks (such as TensorFlow, PyTorch, or OpenAI Gym), cloud platforms, and potentially certifications in AI or data science are common requirements. Creative problem-solving, effective teamwork, and strong communication skills help distinguish top performers in this role. These competencies are essential to designing, implementing, and refining intelligent agents that function reliably in real-world applications.

How to become an AI agent developer?

To become an AI agent developer, you should have a strong foundation in programming languages such as Python, experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of AI concepts such as natural language processing and reinforcement learning. Gaining relevant education through degrees or online courses and building a portfolio of AI projects can also enhance your qualifications.

Is an AI Agent Developer a good career?

An AI Agent Developer is a promising career path in the technology industry, focusing on creating intelligent systems that can perform tasks autonomously. It typically requires skills in programming, machine learning, and AI frameworks, with strong job growth prospects due to increasing demand for automation and AI solutions. The role offers opportunities for innovation and specialization in emerging technologies.

What are the most commonly searched types of Ai Agent Developer jobs in Laurel, MD?

The most popular types of Ai Agent Developer jobs in Laurel, MD are:

What are popular job titles related to Ai Agent Developer jobs in Laurel, MD?

For Ai Agent Developer jobs in Laurel, MD, the most frequently searched job titles are:

What job categories do people searching Ai Agent Developer jobs in Laurel, MD look for?

The top searched job categories for Ai Agent Developer jobs in Laurel, MD are:

What cities near Laurel, MD are hiring for Ai Agent Developer jobs?

Cities near Laurel, MD with the most Ai Agent Developer job openings:

Ai Agent Developer jobs near you
Infographic showing various Ai Agent Developer job openings in Laurel, MD as of August 2026, with employment types broken down into 68% Full Time, 30% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $47,521 per year, or $22.8 per hour.

AI Agent Engineer

Tror AI for everyone

Mclean, VA • On-site

Contractor

Re-posted 12 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