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Internship Generative Ai Prompt Engineer Jobs (NOW HIRING)

Appian Corporation

AI Prompt Engineer

Mclean, VA · On-site

$100K - $225K/yr

We are seeking an AI Prompt Engineer to be the builder behind our "AI-First" transformation. You will be part of the Business Technology AI Engineering team, building production-grade AI solutions ...

Peraton

Generative AI Engineering Intern (Graduate)

$17.25 - $22.25/hr

Interns can support 100% remotely. This open-ended graduate internship is designed to provide ... Support prompt engineering efforts including designing, testing, and refining prompts to improve ...

MDAEdge

Generative AI Engineer

Austin, TX · On-site

... prompt engineering techniques. • Implement few-shot prompting strategies for improved LLM ... Required : • Designed and developed scalable generative AI platforms for enterprise use cases ...

Steampunk

Prompt Engineer

Mclean, VA

$115K - $140K/yr

We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users experience AI ...

Steampunk

Prompt Engineer

Mclean, VA · On-site

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users ...

Steampunk

Prompt Engineer

Mclean, VA · On-site

$115K - $140K/yr

Overview We are seeking a Prompt Engineer design, test, and refine interaction patterns for generative AI systems used across our client engagements. This role is central to shaping how users ...

SS&C Technologies

Key Responsibilities Generative AI & Prompt Engineering * Design, develop, and optimize applications leveraging internal LLM platforms * Create, test, and maintain high-quality prompts to drive ...

HTC Global Services

AI Engineer

Iselin, NJ · On-site

This role focuses on Generative AI, Large Language Models (LLMs), Prompt Engineering, Agentic AI systems, Machine Learning, Data Science, and AWS-based cloud engineering. The ideal candidate will ...

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Internship Generative Ai Prompt Engineer information

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How much do internship generative ai prompt engineer jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for internship generative ai prompt engineer 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.

Can I become an AI prompt engineer with no experience?

Yes, it is possible to become an AI prompt engineer with no prior experience, but developing skills in natural language processing, understanding AI models, and practicing prompt design are essential. Entry-level roles often require self-study, online courses, or tutorials to build foundational knowledge and demonstrate your ability to craft effective prompts.

What is the difference between Internship Generative Ai Prompt Engineer vs Data Analyst?

AspectInternship Generative Ai Prompt EngineerData Analyst
Required CredentialsRelevant coursework, basic understanding of AI and NLPBachelor's in Data Science, Statistics, or related field
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, or tech industries
Employer & Industry UsageAI development, NLP projects, prompt optimizationData collection, analysis, reporting, visualization

While both roles involve working with data and technology, the Internship Generative Ai Prompt Engineer focuses on designing prompts for AI models, whereas a Data Analyst interprets data to inform business decisions. The prompt engineer role emphasizes AI and NLP skills, often in tech environments, while data analysts work across various industries analyzing datasets for insights.

Are AI prompt engineers in demand?

AI prompt engineers are increasingly in demand as organizations seek to optimize generative AI models for various applications. The role requires skills in natural language processing, prompt design, and familiarity with AI tools like GPT, making it a growing field with expanding job opportunities.

How much do AI engineer interns get paid?

AI engineer interns typically earn between $15 and $30 per hour, depending on the company, location, and their level of experience. Internships often provide hands-on experience with tools like Python and machine learning frameworks, and compensation can vary based on the industry and internship duration.

How much do AI prompt engineers get paid?

AI prompt engineers typically earn between $70,000 and $130,000 annually, depending on experience, location, and industry. Entry-level roles may start lower, while experienced prompt engineers working with advanced generative AI models can command higher salaries, especially in tech hubs or specialized sectors.
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Internship Generative Ai Prompt Engineer jobs near you

Generative AI Engineer - McLean, Virginia - Onsite( Local only ) - Inperson interview

Nexylum Global LLC

Mclean, VA • On-site

$100K - $137K/yr

Other

Posted 9 days ago

Job description

Hello
This is Adnan from Nexylum Global Technologies. We are seeking an onsite Senior Generative AI Engineer with over 10 years of experience for a contract opportunity.

We are seeking a highly skilled Generative AI Engineer to design, develop, and deploy cutting-edge AI-powered applications using Large Language Models (LLMs) and modern AI frameworks. The ideal candidate should have hands-on experience building GenAI solutions, integrating AI models with enterprise applications, and developing scalable AI services using cloud platforms.

The candidate will work closely with data scientists, software engineers, and business stakeholders to create intelligent applications such as AI assistants, chatbots, document processing systems, recommendation engines, and workflow automation solutions.

Location: McLean, Virginia - Onsite( Local only ) - In-person interview
Minimum experience required: 10 years

<>Key Responsibilities
  • Design, develop, and deploy Generative AI applications using Large Language Models (LLMs).
  • Build AI-powered chatbots, virtual assistants, document Q&A, summarization, and content generation solutions.
  • Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.
  • Integrate OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, or open-source LLMs into enterprise applications.
  • Create AI agents using frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGen.
  • Fine-tune and optimize LLMs for enterprise-specific use cases.
  • Develop REST APIs and microservices for AI applications.
  • Implement prompt engineering techniques to improve AI model performance.
  • Work with structured and unstructured data for knowledge retrieval and semantic search.
  • Deploy AI applications on cloud platforms such as Azure, AWS, or Google Cloud.
  • Optimize model latency, scalability, and cost efficiency.
  • Ensure responsible AI practices, including security, governance, and compliance.
  • Collaborate with cross-functional teams in Agile/Scrum environments.
  • Stay updated with the latest advancements in Generative AI technologies.
Mandatory Skills<>Generative AI
  • Strong experience with Large Language Models (LLMs)
  • OpenAI GPT Models
  • Azure OpenAI
  • Anthropic Claude
  • Google Gemini
  • Llama, Mistral, or other open-source LLMs
Frameworks
  • LangChain
  • LlamaIndex
  • Semantic Kernel
  • CrewAI
  • AutoGen
  • Hugging Face Transformers
Retrieval-Augmented Generation (RAG)
  • RAG architecture
  • Embedding models
  • Semantic Search
  • Hybrid Search
  • Context Management
Vector Databases
  • Pinecone
  • FAISS
  • ChromaDB
  • Weaviate
  • Milvus
  • Azure AI Search
Programming Languages
  • Python (Mandatory)
  • SQL
  • JavaScript (Preferred)
Machine Learning & AI
  • Prompt Engineering
  • Fine-tuning LLMs
  • NLP
  • Transformers
  • Embedding Models
  • Tokenization
  • Model Evaluation
Cloud Platforms
  • Microsoft Azure
  • Azure OpenAI
  • AWS Bedrock
  • Google Vertex AI
API Development
  • FastAPI
  • Flask
  • REST APIs
  • GraphQL (Preferred)
Databases
  • PostgreSQL
  • MongoDB
  • SQL Server
  • Redis
DevOps & MLOps
  • Docker
  • Kubernetes
  • Git
  • CI/CD
  • MLflow
  • Azure DevOps
  • Jenkins
AI Tools
  • Prompt Engineering
  • AI Agents
  • Function Calling
  • Tool Calling
  • Model Monitoring
  • AI Evaluation Frameworks
  • Guardrails
  • Responsible AI
Version Control
  • Git
  • GitHub
  • Azure DevOps
Methodologies
  • Agile
  • Scrum

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