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Generative Ai Engineer Internship Jobs (NOW HIRING)

United Airlines

AWS Generative AI Engineer

Columbia, SC · Hybrid

$60 - $78.75/hr

We are seeking a highly skilled AWS Generative AI Engineer with strong experience in designing developing and deploying Generative AI solutions on AWS The ideal candidate should possess hands on ...

Socket.dev

Generative AI Engineer, AVP

Jacksonville, FL · On-site

$96.96 - $145.44/hr

Job Summary The USCC Architecture and AI Engineering group is at the forefront of technological innovation, and we are looking for a highly motivated and talented Generative AI/AI Engineer to join ...

IPolarity LLC

Generative AI Engineer

Whippany, NJ · On-site

$70/hr

Generative AI / LLMs * OpenAI / Azure OpenAI * Google AI Stack (Gemini, Vertex AI) * AI Agents & Copilots * Prompt Engineering * RAG (Retrieval-Augmented Generation) * Workflow Automation ...

Black Box

AI Engineer Intern - USA

Plano, TX · On-site

... Generative AI use cases. * Available for a full-time, on-site internship for a minimum of 6-12 ... Programming: Strong working knowledge of Python. * Applied AI / GenAI: Hands-on experience building ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

They are seeking a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. Responsibilities : • ...

Figure

Helix AI Engineer, Generative AI

San Jose, CA · On-site

They are seeking a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand and interact with the physical world, with a focus on training and deploying ...

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Generative Ai Engineer Internship information

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

As of Aug 12, 2026, the average hourly pay for generative ai engineer 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 are the key skills and qualifications needed to thrive in the generative AI engineer internship position, and why are they important?

To thrive as a Generative AI Engineer Intern, you need a solid understanding of machine learning fundamentals, deep learning frameworks, and experience with programming languages such as Python. Familiarity with tools like TensorFlow, PyTorch, and version control systems is often expected, and relevant coursework or certifications in AI or data science are advantageous. Strong problem-solving abilities, communication skills, and eagerness to learn help distinguish top candidates in collaborative, fast-paced environments. These skills are vital for effectively developing, testing, and iterating on generative models that address real-world challenges.

What kinds of projects or tasks do generative AI engineer interns typically work on during their internship?

Generative AI Engineer Interns usually contribute to projects involving model architecture development, data preprocessing, and evaluation of generative algorithms for tasks like text, image, or audio synthesis. Interns often collaborate closely with senior engineers and data scientists, participate in code reviews, and assist in optimizing model performance or preparing proofs of concept for new generative applications. You may also be involved in researching state-of-the-art methods and presenting your findings to the team. These experiences offer valuable hands-on exposure and are designed to prepare you for a future full-time role in AI engineering.

What is a generative AI engineer internship?

A Generative AI Engineer Internship is a temporary position where interns work on developing and optimizing AI models that generate content, such as text, images, or code. Interns typically assist in training, fine-tuning, and testing deep learning models, often using frameworks like TensorFlow or PyTorch. They may also work with large datasets, implement prompt engineering, and collaborate with researchers or engineers. This role provides hands-on experience in machine learning, model deployment, and AI ethics, helping interns build expertise in the field.

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Generative Ai Engineer Internship jobs near you
Infographic showing various Generative Ai Engineer Internship job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $40,174 per year, or $19.3 per hour.

Agentic AI & Generative AI Engineer

Career Soft Solutions Inc

Richardson, TX • On-site

$88K - $121K/yr

Other

Posted 13 days ago

Job description

Job Title: Agentic AI & Generative AI Engineer
Location: Onsite – Richardson,TX/ charlotte, NC
Employment Type: Full-Time / Contract

Job Summary

We are seeking an experienced Agentic AI & Generative AI Engineer to design, develop, and deploy next-generation AI applications powered by Large Language Models (LLMs), autonomous AI agents, and modern AI frameworks. The ideal candidate will have hands-on experience building intelligent AI systems using OpenAI, Anthropic, Gemini, Llama, LangChain, LangGraph, CrewAI, AutoGen, and Retrieval-Augmented Generation (RAG) architectures.

This role involves developing AI agents capable of reasoning, planning, tool usage, memory management, and workflow automation while integrating enterprise data sources and cloud infrastructure.

Key Responsibilities

  • Design, build, and deploy Agentic AI solutions capable of autonomous decision-making and multi-step reasoning.
  • Develop Generative AI applications using Large Language Models (LLMs) such as GPT-4/5, Claude, Gemini, and Llama.
  • Build multi-agent systems using frameworks like LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
  • Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge repositories.
  • Develop AI copilots, intelligent assistants, chatbots, and workflow automation solutions.
  • Integrate AI applications with REST APIs, enterprise applications, databases, and cloud services.
  • Fine-tune prompt engineering strategies to improve response quality, reasoning, and accuracy.
  • Design agent memory, planning, orchestration, and tool-calling capabilities.
  • Deploy AI workloads on Azure, AWS, or Google Cloud using containerized architectures.
  • Optimize inference performance, latency, scalability, and cost.
  • Implement AI governance, security, responsible AI, and compliance best practices.
  • Monitor model performance and continuously improve AI systems using user feedback and evaluation metrics.
  • Collaborate with product owners, architects, data scientists, and software engineers throughout the AI development lifecycle.

Required Qualifications

  • Bachelor''''s or Master''''s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
  • 5+ years of software engineering experience.
  • 2+ years of hands-on experience building Generative AI or LLM-powered applications.
  • Strong programming skills in Python.
  • Experience with OpenAI, Anthropic Claude, Gemini, Llama, or other foundation models.
  • Strong understanding of Prompt Engineering and LLM optimization.
  • Experience building RAG applications.
  • Experience with Vector Databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or Azure AI Search.
  • Experience with LangChain, LangGraph, CrewAI, AutoGen, or Semantic Kernel.
  • Knowledge of embeddings, chunking, semantic search, and retrieval optimization.
  • Experience integrating AI solutions with REST APIs and enterprise applications.
  • Strong understanding of Docker, Kubernetes, CI/CD pipelines, and Git.
  • Experience deploying AI solutions on Azure, AWS, or Google Cloud.

Preferred Qualifications

  • Experience fine-tuning open-source LLMs.
  • Knowledge of Model Context Protocol (MCP).
  • Experience with AI agent orchestration platforms.
  • Familiarity with AI observability tools such as LangSmith, Phoenix, Weights & Biases, or MLflow.
  • Experience with Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
  • Knowledge of knowledge graphs and graph databases (Neo4j).
  • Experience implementing Responsible AI and AI governance frameworks.
  • Experience working with structured and unstructured enterprise data.

Technical Skills

Programming

  • Python
  • SQL
  • JavaScript (preferred)

AI/LLMs

  • OpenAI GPT
  • Anthropic Claude
  • Google Gemini
  • Meta Llama
  • Mistral
  • Hugging Face Transformers

Agentic AI Frameworks

  • LangGraph
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • OpenAI Agents SDK

RAG & Retrieval

  • LangChain
  • LlamaIndex
  • Azure AI Search
  • Pinecone
  • Weaviate
  • Chroma
  • FAISS
  • Milvus

Cloud Platforms

  • Microsoft Azure
  • AWS
  • Google Cloud Platform

DevOps

  • Docker
  • Kubernetes
  • GitHub Actions
  • Azure DevOps
  • Jenkins
  • Terraform

Databases

  • PostgreSQL
  • MongoDB
  • Redis
  • Neo4j

APIs & Integration

  • REST APIs
  • GraphQL
  • MCP
  • Webhooks

Observability

  • LangSmith
  • MLflow
  • Weights & Biases
  • OpenTelemetry

Nice-to-Have Skills

  • AI workflow automation
  • Multi-agent orchestration
  • Human-in-the-loop systems
  • Reinforcement learning concepts
  • AI safety and governance
  • Prompt optimization and evaluation
  • Knowledge graph integration
  • AI-powered business process automation

Soft Skills

  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration abilities.
  • Ability to translate business requirements into AI-driven solutions.

Apply