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Intern Ai Agent Developer Jobs in Silver Spring, MD

Appian Corporation

AI Security Engineer

Mclean, VA

AI Security Engineer (Agentic SOC)In this role, you will: * Build & Deploy Agents: Design, test ... You understand that an AI agent is only as good as the guardrails keeping it from deleting a ...

Accenture Federal Services

AI Engineer

Washington, DC · On-site

The AI Engineer will build AI systems for scientific discovery, develop conversational interfaces ... agent frameworks supporting scientific discovery in areas like subsurface geology, supply chain ...

Recorded Future

Senior Software Engineer

Washington, DC · On-site

$138K - $182K/yr

... AI Agent solutions across the platform. • Drive engineering excellence by conducting rigorous code reviews, focusing on code quality, performance optimization, and operational maturity. • Lead ...

HCI

AI Summer Intern

Ellicott City, MD

$15 - $20/hr

AI Intern 2026 AI Developer Intern -- 60-90 Day Summer Internship What We're Looking For HCIactive is a forward-thinking, highly experienced AI development organization that has fully transformed ...

AHU Technologies Inc

AI Builder

Washington, DC · On-site

$140K - $300K/yr

... grade AI agent systems. The ideal candidate will combine machine learning, software engineering, and product thinking to build reliable AI solutions that solve complex business problems.

New

Lightedge

Sr. AI Integration Engineer

Ashburn, VA

$106K - $143K/yr

AI Agent, Harness & Workflow Development: Design, develop, and maintain production-grade AI agents ... Engineering Standards: Contribute to codebases, deployment pipelines, support practices, and ...

Lightedge

Sr. AI Integration Engineer

Ashburn, VA · On-site

$106K - $143K/yr

AI Agent, Harness & Workflow Development: Design, develop, and maintain production-grade AI agents ... Engineering Standards: Contribute to codebases, deployment pipelines, support practices, and ...

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All JobsIntern Ai Agent Developer JobsIntern Ai Agent Developer Jobs in Silver Spring, MD

Intern Ai Agent Developer information

What does an Intern AI Agent Developer do?

An Intern AI Agent Developer assists in designing, developing, and testing artificial intelligence agents, which are software programs capable of performing tasks that typically require human intelligence. Their responsibilities may include writing code, training machine learning models, analyzing data, and supporting senior developers in research or project work. Interns in this role gain hands-on experience with AI frameworks and tools while learning best practices in software engineering and artificial intelligence development.

What types of projects and tasks can an Intern AI Agent Developer expect to work on during their internship?

As an Intern AI Agent Developer, you will typically collaborate with experienced engineers and data scientists to design, develop, and test components of AI-driven systems. Your daily tasks may include writing and debugging code, assisting in training machine learning models, and running experiments to evaluate agent performance. Interns often contribute to documentation, participate in code reviews, and may even help implement features under supervision. This role provides a hands-on learning environment where you can develop both technical and teamwork skills, while gaining exposure to the latest AI development tools and practices.

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

AspectIntern Ai Agent DeveloperIntern Machine Learning Engineer
Required CredentialsRelevant coursework, basic programming skills, familiarity with AI toolsRelevant coursework, programming skills, understanding of ML algorithms
Work EnvironmentTech companies, AI startups, research labsTech companies, research institutions, AI startups
Employer & Industry UsageAI development teams, chatbot and virtual assistant projectsData science teams, predictive modeling projects

Intern Ai Agent Developers focus on building and improving AI agents like chatbots and virtual assistants, often requiring knowledge of AI frameworks. Intern Machine Learning Engineers work on developing ML models for various applications, emphasizing data handling and algorithm implementation. Both roles are common in tech and AI industries, but they differ in specific focus areas and skill sets.

What are the key skills and qualifications needed to thrive as an Intern AI Agent Developer, and why are they important?

To thrive as an Intern AI Agent Developer, you need a solid understanding of programming languages like Python, basic knowledge of machine learning concepts, and enrollment in or completion of a relevant degree such as computer science. Familiarity with tools and frameworks such as TensorFlow, PyTorch, Git, and cloud platforms is typically expected. Curiosity, strong problem-solving skills, and the ability to collaborate within a team help you stand out. These skills are crucial for successfully contributing to AI projects, learning quickly in a dynamic field, and effectively supporting development teams.
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Intern Ai Agent Developer jobs near you
AI Security Engineer

AI Security Engineer

Appian Corporation

Mclean, VA

Other

Posted 8 days ago

Job description

 AI Security Engineer (Agentic SOC)In this role, you will:

  • Build & Deploy Agents: Design, test, and deploy autonomous and semi-autonomous AI agents that integrate natively with our enterprise security stack (SIEM, EDR, XDR, and Threat Intel feeds).

  • Code the Playbooks: Translate traditional, human-centric SOC playbooks and analyst workflows into deterministic and heuristic agentic pipelines (using DAGs and multi-agent routing).

  • Optimize RAG Pipelines: Design, optimize, and maintain production-grade Retrieval-Augmented Generation (RAG) workflows to inject real-time security context, network topology, and historical incident logs into agent prompts.

  • LLM Performance Engineering: Continuously evaluate, benchmark, and optimize LLM performance, context window utilization, latency, and cost-efficiency across various models (OSS and commercial).

  • Design Human-in-the-Loop (HITL): Collaborate deeply with Tier 3 Analysts and Threat Hunters to engineer seamless HITL handoff mechanisms, ensuring agents safely escalate complex anomalies to humans.

  • Secure the AI: Implement robust security boundaries around our LLM architecture, mitigating risks like prompt injection, data poisoning, model tool-abuse, and addressing the OWASP Top 10 for LLMs.

The Ideal Candidate:

  • You are a Builder First: You take immense pride in shipping clean, production-grade, asynchronous code. You care about system architecture as much as model accuracy.

  • Security-Curious or Security-Hardened: You bridge the gap between AI research and practical cybersecurity. You understand that an AI agent is only as good as the guardrails keeping it from deleting a production server during a false positive.

  • Thrives in Ambiguity: Building an Agentic SOC means charting unknown territory. You love breaking down abstract, high-level security problems into concrete, execution-ready AI systems.

Basic Qualifications:

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies, OR a Master's degree in a related field plus at least 2 years of experience.

  • At least 2 years of experience programming with Python, Go, Scala, or Java.

Preferred Qualifications:

  • 3 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure).

  • Experience designing, developing, delivering, and supporting AI services, specifically within the domains of security operations or threat intelligence.

  • Hands-on experience building multi-agent or complex orchestration systems using tools such as LangChain, LlamaIndex, AutoGen, CrewAI, or Semantic Kernel.

  • Proven experience working with production Vector Databases (e.g., Pinecone, Qdrant, Milvus, or Weaviate) for semantic chunking, embedding generation, and metadata filtering.

  • Experience deploying and scaling AI workloads in containerized cloud environments (AWS, Azure, or GCP using Kubernetes/EKS/AKS).

Are you ready to build the future of autonomous, agentic defense? 

Apply