JobTarget is a leading company in the online job search and recruiting industry. Our team is comprised of experts in recruitment, e-commerce, and online job search. Our products are used by thousands of corporate recruiters and reach millions of job seekers. The company values work-life balance, rewarding risk and creativity, and an open culture. driven, and open-minded. We're perpetually searching for ways to make the job search process better, so if you're up for the challenge, apply, and let's make it better together.

The Opportunity
We are looking for a motivated Generative AI Developer Intern to join our AI Engineering Team. In this role, you will help design, build, test, and improve AI-powered applications and internal tools using modern software engineering practices. You will work closely with software engineers, AI/ML engineers, product managers, and data teams to develop prototypes, integrate large language models, build APIs, evaluate model outputs, and contribute to production-quality AI features. This internship is ideal for students or recent graduates with a strong computer science background, solid coding skills, and an interest in building practical applications using generative AI technologies. Must be able to work at least 30 hours a week.

Responsibilities

Develop and maintain AI-powered software features, prototypes, and internal tools.
Write clean, efficient, and well-documented code in Python or another modern programming language.
Integrate large language models and AI APIs into applications, workflows, or backend services.
Assist in building retrieval-augmented generation, prompt workflows, model evaluation pipelines, and AI agent workflows.
Support development of agentic AI applications using frameworks such as LangGraph, LangChain, or similar tools.
Collaborate with engineers to design APIs, services, and data flows that support AI applications.
Test, debug, and improve AI system behavior, including accuracy, reliability, latency, and usability.
Participate in code reviews, unit testing, documentation, and deployment activities.
Help evaluate AI outputs for quality, consistency, safety, and business usefulness.
Work with structured and unstructured data, including text, documents, logs, or user-generated content.
Stay current with emerging AI development tools, frameworks, and best practices.

Required Qualifications

Currently pursuing a Bachelor’s or Master’s degree (preferred) in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
Strong programming skills in Python, JavaScript/TypeScript, Java, or a similar language.
Solid understanding of data structures, algorithms, object-oriented programming, and software engineering fundamentals.
Experience building software projects, APIs, applications, automation scripts, or backend services.
Familiarity with REST APIs, JSON, Git, and basic cloud or deployment concepts.
Strong analytical and problem-solving skills.
Ability to learn quickly, communicate clearly, and work well in a collaborative engineering environment.

Preferred Qualifications

Experience with generative AI tools, LLM APIs, or AI application frameworks.
Familiarity with tools or concepts such as: OpenAI, Anthropic, Gemini, Azure OpenAI, or similar LLM platforms LangGraph, LangChain, LlamaIndex, Semantic Kernel, or similar AI application frameworks
AI agents, multi-step workflows, tool calling, memory, routing, or orchestration patterns
Vector databases such as Pinecone, Weaviate, Chroma, FAISS, or pgvector
Retrieval-augmented generation, embeddings, prompt engineering, or model evaluation
FastAPI, Flask, Node.js, React, or similar application frameworks
Docker, CI/CD, cloud platforms, or basic DevOps workflows
Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
Experience working on academic, personal, open-source, or internship projects involving AI, ML, NLP, automation, or software development.
Interest in responsible AI, model evaluation, privacy, security, and safe AI deployment.

What You’ll Learn

How to build real-world generative AI applications and AI-powered developer tools.
How to integrate LLMs into software systems using APIs, embeddings, retrieval, and evaluation workflows.
How to design AI agent workflows using tools such as LangGraph and related frameworks.
Best practices for writing production-quality code for AI applications.
How to test and improve AI system reliability, accuracy, and performance.
How AI engineering teams collaborate across product, data, software, and infrastructure functions.
Practical exposure to modern AI development frameworks, cloud tools, and deployment practices.

Hourly pay range: $27.00 - $30.00. JobTarget is an equal-opportunity employer.

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