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What is a masters in artificial intelligence?

A Masters in Artificial Intelligence is a graduate-level degree program that focuses on teaching students advanced concepts and techniques in AI, including machine learning, deep learning, natural language processing, robotics, and data science. The program is designed to equip students with both theoretical knowledge and practical skills needed to develop intelligent systems and solve real-world problems using AI technologies. Graduates are prepared for careers in industries such as technology, healthcare, finance, and academia, or for pursuing further research in the field.

What are the key skills and qualifications needed to thrive with a masters in artificial intelligence?

To thrive with a Master's in Artificial Intelligence, you need a solid background in mathematics, programming (often Python), and machine learning principles, supported by an advanced degree in AI or a related field. Familiarity with tools such as TensorFlow, PyTorch, and cloud computing platforms, as well as knowledge of data analysis and visualization systems, is typically required. Strong problem-solving abilities, creativity, and effective communication skills help you design solutions and present technical concepts to diverse audiences. These competencies are crucial for developing innovative AI systems, collaborating across teams, and driving impactful technology projects.

How does earning a masters in artificial intelligence impact opportunities for interdisciplinary collaboration in professional settings?

A Master's in Artificial Intelligence uniquely positions professionals to collaborate across diverse teams, including data scientists, software engineers, and domain experts in areas like healthcare, finance, or manufacturing. Graduates often find themselves bridging gaps between technical and non-technical stakeholders, translating complex AI concepts into actionable business solutions. This interdisciplinary environment enhances problem-solving skills and offers exposure to a wide range of real-world challenges, fostering both personal and career growth. Such collaboration is highly valued by employers, as it drives innovative solutions and helps integrate AI technologies into various industries.

Is it worth doing a master's in artificial intelligence?

A master's in artificial intelligence prepares individuals for roles such as AI engineer or data scientist, offering advanced knowledge in machine learning, programming, and data analysis. It can improve job prospects and earning potential, especially in industries adopting AI technologies, but the value depends on career goals and industry demand.

What can I do with a master's in artificial intelligence?

A master's in artificial intelligence prepares graduates for roles such as AI engineer, data scientist, machine learning engineer, or research scientist. These positions involve developing algorithms, building models, and applying AI techniques using tools like Python, TensorFlow, or PyTorch in various industries including tech, healthcare, finance, and robotics.

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Masters In Artificial Intelligence jobs near you
Infographic showing various Masters In Artificial Intelligence job openings in Virginia as of August 2026, with employment types broken down into 74% Full Time, and 26% Part Time. Highlights an 90% In-person, and 10% Remote job distribution.

Artificial Intelligence & Cloud Engineer

Norfolk, VA • On-site

Vets Hired
Recruiting and Staffing Services • 51 - 200 employees
Learn more about Vets Hiredexternal

$54 - $72/hr

Other

Posted 12 days ago

Job description

Job Summary

The Artificial Intelligence & Cloud Engineer designs, builds, secures, and scales AI-powered systems within cloud environments. The role combines artificial intelligence, machine learning, cloud engineering, software development, retrieval systems, multi-agent architectures, vector databases, and secure AI deployment. The engineer will develop production-grade AI applications and microservices while collaborating with data scientists, designers, and subject matter experts in an Agile environment.

Key Responsibilities
  • Architect and implement scalable multi-agent AI systems.
  • Develop advanced routing and hierarchical multi-agent architectures.
  • Build, optimize, and maintain production-grade Retrieval-Augmented Generation (RAG) pipelines.
  • Develop semantic search and information retrieval systems.
  • Design data preprocessing workflows, chunking strategies, and vector database infrastructure.
  • Deploy, secure, monitor, and maintain AI applications and microservices in cloud environments.
  • Integrate AI capabilities into user-facing products.
  • Collaborate with data scientists, UI/UX designers, and subject matter experts.
  • Establish security best practices for large language model implementations.
  • Protect sensitive information through secure data handling and privacy controls.
  • Implement AI model guardrails and other AI security measures.
  • Develop robust RESTful APIs supporting AI and cloud applications.
  • Support Linux-based development and cloud environments.
  • Apply text analytics, prompt engineering, data normalization, and data-cleaning techniques.
  • Support cybersecurity risk management and system hardening activities.
  • Evaluate and adopt emerging AI technologies and engineering practices.
Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
  • 7+ years of professional software engineering experience.
  • At least 2 years of production experience in AI, ML, or NLP development.
  • Experience building multi-agent systems using LangGraph, AutoGen, or equivalent frameworks.
  • Strong understanding of RAG architecture, vector databases, embeddings, and information retrieval.
  • Strong programming skills in Python or a similar programming language.
  • Experience developing RESTful APIs.
  • Hands-on experience deploying and managing AWS or OCI cloud services.
  • Proficiency with Linux operating systems and command-line interfaces.
  • Expertise in text analytics and prompt engineering.
  • Experience with data normalization and cleaning.
  • Active Secret security clearance.
  • Current CompTIA Security+ certification or higher.
  • Knowledge of AI security practices, model guardrails, and secure data handling.
  • Experience working in Agile and cross-functional development environments.
  • Strong problem-solving skills and ability to learn emerging AI technologies quickly.
Preferred Qualifications
  • Experience with NAVSEA Cyber RMF processes and system security hardening.
  • Familiarity with Rust, Go, or JavaScript.
  • Industry-recognized cloud certifications, such as AWS Certified Machine Learning - Specialty or OCI AI credentials.
  • Experience with open-source LLM evaluation and observability frameworks.
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