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Prompt Engineering Internship Jobs (NOW HIRING)

... internships/projects accepted). * Strong Python and SQL skills. * Familiarity with LLMs, RAG, Prompt Engineering, and ML fundamentals. * Experience with PyTorch/TensorFlow and Git. Preferred

Support the development of AI agentic components such as task planning, tool use, memory, prompt ... Previous projects or internship experience involving machine learning or AI (especially work with ...

Support the development of AI agentic components such as task planning, tool use, memory, prompt ... Previous projects or internship experience involving machine learning or AI (especially work with ...

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Prompt Engineering Internship information

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$11

$19

$29

How much do prompt engineering internship jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for prompt engineering internship in the United States is $19.31, according to ZipRecruiter salary data. Most workers in this role earn between $16.11 and $20.91 per hour, depending on experience, location, and employer.

What is the stipend for prompt engineer intern?

The stipend for a prompt engineering internship varies depending on the company and location but typically ranges from $1,000 to $3,000 per month. Interns often work part-time or full-time and may also receive mentorship and skill development opportunities.

What is a Prompt Engineering Internship job?

A Prompt Engineering Internship is a role where interns learn to design, refine, and optimize prompts for AI models to generate accurate and useful responses. Interns work closely with developers, researchers, and data scientists to test and improve AI outputs. The position often involves experimenting with different prompt structures, analyzing results, and helping enhance AI capabilities. This internship is ideal for those interested in AI, natural language processing, and machine learning applications.

Is 22 too old for an internship?

Prompt Engineering Internships are open to candidates of various ages, including those in their early twenties. Age is generally not a barrier, and employers often value skills, relevant experience, and a willingness to learn over age. Many internships welcome diverse applicants, regardless of age, especially if they demonstrate enthusiasm and technical aptitude.

What kinds of projects or responsibilities can I expect during a Prompt Engineering Internship?

As a Prompt Engineering Intern, you will typically work on developing, testing, and optimizing prompts for large language models to improve response quality and accuracy. Your daily tasks may include collaborating with engineers, data scientists, and product teams to understand project goals, conducting experiments to evaluate prompt effectiveness, and documenting findings or best practices. You may also be involved in researching emerging trends in AI and suggesting improvements based on real-world feedback. This role offers a dynamic environment with opportunities to contribute to cutting-edge applications and strengthen your technical and communication skills in a collaborative team setting.

What are the key skills and qualifications needed to thrive in the Prompt Engineering Internship position, and why are they important?

To thrive as a Prompt Engineering Intern, you need a strong background in language modeling, natural language processing (NLP), and analytical thinking, often supported by coursework or experience in computer science or related fields. Familiarity with tools like Python, machine learning libraries (such as TensorFlow or PyTorch), and platforms that host large language models (like OpenAI API) is helpful. Excellent communication, problem-solving abilities, and creativity are valuable soft skills for crafting effective prompts and collaborating within teams. These skills ensure that prompts are precise and effective, enabling high-quality outputs from AI systems and driving innovation in conversational AI applications.

What jobs can I get with prompt engineering?

Prompt engineering skills are valuable in roles such as AI/ML engineer, data scientist, NLP specialist, or AI product manager, where designing effective prompts improves AI model outputs. These positions often require knowledge of machine learning, programming, and AI tools like language models. The role involves developing, testing, and refining prompts to optimize AI performance in various applications.

Are prompt engineers still in demand?

Prompt engineering is a growing field as AI language models become more integrated into various industries. Demand for prompt engineers is increasing, especially for roles involving AI development, natural language processing, and expertise with tools like GPT models, making it a valuable skill set for tech-focused positions.
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Infographic showing various Prompt Engineering Internship job openings in the United States as of June 2026, with employment types broken down into 1% Internship, 56% Full Time, 25% Part Time, 2% Temporary, and 16% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.
Federal AI Solutions Engineer (Entry Level)

Federal AI Solutions Engineer (Entry Level)

A-TEK Inc.

Mclean, VA

$85K - $105K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 23 days ago


Job description

A-TEK is seeking an early-career Federal AI Solutions Engineer to support the design, development, and deployment of mission-focused AI and cloud solutions across AWS and Azure environments. This role is ideal for recent graduates with a strong academic foundation in Artificial Intelligence, Machine Learning, software engineering, and cloud technologies who are eager to apply their skills to real-world federal mission challenges.

The engineer will work alongside senior architects and engineers to develop AI-enabled applications, cloud-native solutions, automation workflows, and rapid prototypes that support A-TEK's DigitalShift innovation initiatives.

This is a hybrid role based in McLean, VA. No visa sponsorship is available for this role. This role requires the ability to obtain and retain a public trust level security clearance.

Key Responsibilities

AI Solution Development

  • Assist in the design, development, and deployment of AI-powered applications and prototypes using:
    • AWS Bedrock
    • Azure OpenAI
    • LangChain, LlamaIndex, Semantic Kernel, CrewAI, or similar frameworks
  • Develop and test prompt engineering strategies, retrieval-augmented generation (RAG) workflows, and AI agent capabilities.
  • Support integration of AI solutions with APIs, enterprise systems, and cloud services.

Cloud Engineering

  • Build and maintain cloud-based environments in AWS and Azure.
  • Assist with infrastructure deployment using Infrastructure-as-Code tools such as Terraform, AWS CDK, or Bicep.
  • Support containerized deployments using ECS, EKS, or AKS.
  • Participate in CI/CD implementation and cloud automation efforts.

Technical Support & Innovation

  • Support senior engineers in troubleshooting cloud, AI, and data integration challenges.
  • Assist in developing reusable templates, accelerators, and reference architectures.
  • Participate in rapid prototyping efforts that demonstrate mission value for federal customers.

Collaboration & Knowledge Sharing

  • Collaborate with Cloud, Cybersecurity, Data Intelligence, and Agile Engineering teams.
  • Contribute to technical documentation, architecture diagrams, and knowledge-sharing initiatives.
  • Stay current with emerging AI, machine learning, and cloud technologies.

Security & Compliance

  • Support implementation of solutions that align with:
    • NIST AI Risk Management Framework (AI RMF)
    • FedRAMP requirements
    • Zero Trust principles
    • Secure coding and responsible AI practices

Required Qualifications

Education (Required)

Bachelor's degree in Computer Science with a concentration, specialization, minor, or significant coursework in Artificial Intelligence, Machine Learning, Data Science, or a closely related field.

Experience

  • 0-2 years of professional software engineering, AI/ML, or cloud development experience.
  • Relevant internships, research projects, capstone projects, graduate assistantships, or co-op experience may be substituted for professional experience.
  • Demonstrated programming experience in Python through coursework, projects, internships, or employment.

Technical Skills

  • Foundational understanding of machine learning, generative AI, and large language models.
  • Experience using cloud platforms (AWS or Azure) through coursework, internships, certifications, or projects.
  • Familiarity with:
    • REST APIs
    • Git version control
    • Containerization concepts
    • Data pipelines and databases
  • Understanding of prompt engineering, RAG concepts, or AI agents through academic or personal projects.
  • Strong analytical and problem-solving skills.

Certifications

One of the following is preferred within the first year of employment:

  • AWS Certified Cloud Practitioner or AWS Solutions Architect Associate
  • Microsoft Azure Fundamentals (AZ-900) or Azure AI Fundamentals (AI-900)

Preferred Qualifications

  • Academic or project experience with:
    • LangChain
    • LlamaIndex
    • Semantic Kernel
    • CrewAI
  • Exposure to vector databases such as Pinecone, Weaviate, FAISS, or Milvus.
  • Experience building AI, machine learning, or cloud-based capstone projects.
  • Familiarity with DevOps, MLOps, or CI/CD concepts.
  • Interest in federal government missions and emerging AI technologies.

Compensation

Salary Range

$85,000 - $105,000 annually

Salary will be determined based on education, certifications, internship experience, technical proficiency, and security clearance eligibility.

Benefits

  • Medical, Dental, and Vision Insurance
  • 401(k) with Employer Match
  • Paid Time Off and Federal Holidays
  • Professional Development and Certification Reimbursement
  • Career Growth and Mentorship Opportunities